Study And Analysis On The Banking Sector Finance Essay - Free Essay Example

Sample details Pages: 20 Words: 6087 Downloads: 4 Date added: 2017/06/26 Category Finance Essay Type Research paper Did you like this example? A vibrant and proactive sector on which the economy of any nation depends on is the banking sector. The Banking sector thrives on the provision of an enabling environment for business transactions and further improvement of its services portfolio to its customers. Strategic planning in the banking sector encourages bank growth which affect prosperity; it involves a long term planning taking into attention, The Banking sector represents a trading unit of an economy. Don’t waste time! Our writers will create an original "Study And Analysis On The Banking Sector Finance Essay" essay for you Create order It strives on providing an enabling environment for business transaction and continuous improvement of its customer services. Strategic planning in banking enhances the growth of banks, which subsequently effects prosperity. It involves a long term planning with consideration for opportunities and threats posed by the external environment. In order for banks to achieve its objectives effectively and to ensure the satisfaction of its clients, well defined strategies are required during decision making and policy formulation/application. Katuri(2005, p.1) state that advancements in technology however, has brought about a paradigm shift from traditional banking practices by banks to offering Internet based banking services such as Automated Teller machine [ATM], Electronic banking ,Mobile Banking which collectively ease difficulty in banking like cost effectiveness and timely delivery of transactions other products and services As further emphasized by Nair (2005, p.151), the usef ulness of information technology in the field of banking has become intensive. Nair (2005) also opines that technology has become an enabler for the needs of customers and banks to be met especially, as needs of customers lifestyle keep changing overtime. The growth of technology has bridged the bottlenecks in product delivery to customers. Nair (2005) believes the embracing of technology by banks as a strategic and calculated attempt to improve productivity, profits, reduction of operational cost and efficiency. ABA (2004) and Fox (2005) likewise believe that electronic banking services rendered by the banking sector are often customized towards the retention of existing customers, acquisition of new customers and ultimately improvement in productivity levels, so as to gain a competitive edge in customer retention over traditional banks (who do not readily embrace e-banking). The utmost concern in a world of developed information technology is how the gap of time, distance ca n be bridged while at the same time maintaining effectiveness and accuracy. New trends in information technology have indicated that barriers such as time and distance could be bridged while effectively maintaining efficiency in the provision of banking services to customers. The age of internet explosion has been a great relief to the factors constraining the effectiveness and awareness in both social and transaction world. Ganti (2005, p.56) stated that the introduction of -banking shows a paradigm shift in the customer relationship marketing environment for banks. It has repositioned the modern banking sector, subsequently creating unlimited opportunities with customers becoming sophisticated. In the transactional world, the era of internet explosion has tremendously improved the banking sector through the system Known as ELECTRONIC BANKING. In recent years the Banking sector witnessed the coming of age in Electronic banking and decline of traditional way of banking practi ces, research carried in 2004 by American bankers Association[ABA] evidence shows that banks offering electronic based banking services gain higher advantage in servicing banking. Electronic banking usage by banks are targeted at reducing operational cost thereby sustaining efficiency and increasing market share while retaining its customers (ABA 2004, Fox 2005).Despite the explosion, a new market based services is being offered by Electronic banking. The Stewart Brandley (2002) in their case study titled A delphi study of drivers and inhibitors of internet banking indicates that countries of the world have been able to embrace the system; while some countries have advanced tremendously, others are yet struggling with constraints. The advanced countries known as technologically developed nations such as UK and USA have maximized the potentials of Information Technology in banking while developing countries such as Nigeria and Egypt are yet to fully adopt the new trend i n banking technology. Ovia (2001) states that the factors constraining the growth of Electronic banking in developing countries are: Illiteracy Poor infrastructure: High cost of Telecommunication Power supply Security Lack of awareness Illiteracy The above listed constraints are huge impediments towards the adoption of e-banking in Nigeria. The study about Nigeria shows pinpoints the majority of Nigerian nationals as rural dwellers, therefore a good enlightenment campaign will result in a remarkable increase in the banking sector and the subsequent usage of electronic banking service offerings. However, it is worthy to categorically state that technological advancement has been a major driving force of GLOBALISATION. The effects of globalization on e-banking is such that technology-related advancements achieved via e-banking has provided a solution to the problems of distance and time subsequently ensuring that customers can transact business and gain acce ss to new markets easily. 1.2 AIMS AND OBJECTIVES 1.2.1 AIMS The study aims to identify and discuss the impact of information technology on customers in the retail banking industry with special emphasis on the Nigerian environment as a case study. Also, factors that influence the customers in the adoption of technology, low awareness levels of technological offerings will be discussed. The affinity of Nigerian banks toward the information technology platform would also be considered. 1.2.2 OBJECTIVES Definition of e-banking and the analysis of the advances in e-banking since its introduction in the Nigerian banking industry. Identification of the advantages e-banking brings to the banking industry. Discussion of the effect e-banking has on customers and an insight into their level of electronic usage or experience. Research and analysis of e-banking products/services/portfolio provided by banks to their customers. Identify reasons for under-development of e-banking in Nigeria To make recommendations for the modernization and development of the e-banking platform. 1.3 MOTIVATION BEHIND RESEARCH TOPIC In recent years the technological advancements has necessitated the move towards technological development in Nigeria. It is a developing country with a population of about 140 million people, and its a country with huge telecommunication growth in Africa over the past 10 years. The country has experienced an impressive level of development in tele-density (number of telephone lines per population unit, usually 100 people) from a tele-density of 0.73 in 2001 to 46.80 in 2009 (Nigeria Communications Commission [NCC], 2009). The explosion in tele-density has immensely improved the growth rate obtained in various industries. However, despite the explosion in telecommunication activities in the Nigerian environment, Nigeria is still to meet up with the advancement in technology like other developed countries such as the United kingdom. However, (Ovia,2001) also believes that the move towards technological advancement is hampered due to lack of proper infrastructure such as power supply, communication and security is also a major problem. These are recognized as potentially huge impediment to the economic development and advancement in technology 1.4 SIGNIFICANCE OF RESEARCH TOPIC The importance of this research is such that it emphasizes the merits and demerit of e-banking in the Nigerian retail banking industry. Subsequently, information gathered and researched would provide a good starting point towards suggestions on the improvement of banking services in Nigeria, but most importantly the formulation and implementation of policies that will incorporate technological improvements such as e-banking in the pot-pourri of banking services available to the Nigerian public. The Nigerian banking sector has not been spared with the banking boom era of the 90s which did not last long- a situation which saw many banks closing down and the eventual loss of public confidence in the banking industry, consequently leading to the creation of the failed bank tribunal by the government. The banking boom is back but the banks are facing stiff competition in retaining their customers, their customer retention ability will depend on the information technology infrastru cture available. However, global recession in 2008 was marked coincidentally by failures of banks and unstable slip in economic statistics. Based on these premise, the global recession will not affect e-banking services in Nigeria due to its relatively new introduction to the Nigerian retail banking industry, and as illustrated by Fox (2005) and ABA (2004) evidence proves that banks offering these internet based pot-pourri of services are better positioned in retaining customers than traditional non electronic banking banks. 1.5 PROJECT CONSTRAINTS Time: Availability of time will be at a premium all through the duration of the project. Factors to also consider in the estimation of available time towards the project are coursework from other taught units and examinations. Non-commitment from respondents: Low or no response from client that are to be interviewed or not getting the information needed because is view as classified documents by the client company. Also respondents not returning questionnaires are a major constraint. 1.6 RESEARCH METHODOLOGY The research methods that will be adopted are the primary and secondary data methods. Primary research method will involve the use of surveys for data collection: statistical data. The research technique shall be questionnaires given out randomly to people in the Lagos metropolis and bank personnel. However, the secondary research shall be based on data collection from different websites of banks and on existing factors to support the research work. Also, the University library and the internet will be a major source of information. 1.7 STRUCTURE OF THE PROJECT This research begins with an introduction in chapter 1. Chapter 2 centers on the review of related literature. Subsequently, it covers detailed explanation on facts outlined, advantages and disadvantages. Chapter 3 shall explain the different research methodologies and reasons for using the chosen methodology. The evaluation of secondary research will be included. And chapter 4 shall give a full analysis and interpretation of results from primary research information and the future of electronic banking in Nigeria. While chapter 5 shall look at the research findings and chapter 6 looks at the conclusion and recommendations. METHODOLOGY 3.1 RESEARCH METHODS The research methodology is classified into two groups and the information gathered is analyzed as quantitative or qualitative data. PRIMARY RESEARCH The primary research involves communicative interaction with people. The information gathered will be analyzed to ensure its usefulness to answer the research question and for the research purpose. The information needed will be collected by questionnaire surveys, focus group, content analysis and observation. SECONDARY RESEARCH The secondary research entails the processing of information that has been previously analyzed and used for further analysis. This information can be assembled from prior research studies, journals, books, articles and online materials. Both methods have advantages and disadvantages and the suitable approach is to understand the rationale for the evaluation of the survey, the required information and the number of respondents required to arrive at a conclusion on research findings. The credibili ty and date of publication must also be put into consideration when applying secondary data to avoid erroneous outcomes. Since the main aim of the research is to select a method that meets the research objectives, secondary data may not have dealt with the current topic or may be outdated so it is essential for a primary research. That notwithstanding, some disadvantages of the primary method is it is time consuming because information is critically analyzed to get accuracy in results. 3.2 METHOD CHOSEN With regards to this research, both methods were used because Electronic banking is still relatively new in contemporary networking circles and previous research in this area is limited in comparison to other related topics. One reason for choosing the primary data is because it is believed to be versatile and flexible in nature. The performance ordinarily has a more profound effect on the survey results than has any other single element of survey (Alreck Settle 2004, p.89). While secondary research allows for comparism of data collected from previous studies, they are required for guidance of the primary research (Frankfort Nachmias 1996, p.306). However the use of only secondary research will not give the required results. Through secondary research, banks adoption of Electronic banking in relation to the level of customer adoption and service rendered and the evaluation of secondary research data have aided in scrutinizing problems associated with the research topic. Furthe rmore, analyzing to what extent Electronic banking is adopted by Nigerian banks and customers level of adoption of these services. Valuable information was retrieved from secondary research in the analysis of the research topic. However, some limitations were that collated data was not enough to summarize and draw conclusions and so the use of primary method (Questionnaire) was applied to ascertain the authenticity of information obtained from secondary data was accurate. However the limitation of using a primary research is slow response from respondents and some not even returning the questionnaire. The objectives of the primary research is To identify the level of adoption of customers to Electronic banking. To research and analyze the degree of Electronic banking services offered by banks. The questionnaires were distributed via email. Another format for this was personal interview with banks with some open ended questions such as What measures are on ground to en hance internet banking security? This allowed for respondents to answer the questions freely without restriction of options. The information retrieved was accurate because all banks have distinctive security software in operation. The second format, the close ended questionnaire, was for respondents to fill, with a number of options to choose from. This is fast and easy to return without delay. 3.3 THE RESEARCH PLAN The research plan is a blueprint of sampling unit, sampling frame, sampling procedures and design. The sample unit was in form of a survey carried out within the heart of commerce in Nigeria, Lagos state. The sampling frame comprises of all the banks in the Lagos metropolis and with a sample size of 10 to enable good response for accuracy than loads of questionnaires filled incorrectly. The method used was stratified sampling to ensure diverse groups of people were well represented in the sample and to also increase accuracy level in the estimation of parameters. The sampling procedure was in two parts with focus aimed at two groups. The first is the service provider i.e. the banks, comprising of the old and new generation banks. The second is the service users i.e. customers. The total of questionnaires that were distributed was 80 and 68 was returned. The questions were directed toward the students, working class and to the general public as well as tailored questions towards int ernet usage accessibility and electronic banking service awareness. The researcher gathered useful information with the adoption of this method and the same question was sent to all respondents for ease of analysis and because the viability and reliability of a research study largely depends on information consistency to obtain reliable results. 3.4 ANALYSIS OF SECONDARY DATA Data assembled from previous research was beneficial in evaluating the research topic. When considering secondary research, the data analyzed does not meet the researchers need as results were not completely accurate in fulfilling the aims of the research. Despite this limitation, a careful examination was made to ensure that data collected were from sources that could justify precise information and to also ensure accurate documentation of findings is presented correctly after evaluation. The secondary data was analysis on works done at Nigerian institutions, Obafemi Awolowo University and the University of Benin. However, the research aim differs from the research project as the focus was Electronic banking in Nigeria. Nonetheless, important information was retrieved for the aim of drawing conclusions. 3.5 SUMMARY In the methodology chapter, the various available research methods have been examined and have been used to justify a chosen method. A sample size would have generated a more accurate result but despite this and the limitations faced, evaluating secondary data has assisted in consolidating research findings. RESEARCH ANALYSIS 4.1 INTRODUCTION In this chapter, analysis will be carried out on data that are gathered from the survey findings. Primary data of Questionnaire A was to the service users or exploiters. This was oriented for the accessibility of the internet and having knowledge of electronic banking. And Questionnaire B of the primary data was to the service supplier or providers. And to analyse the secondary data and equating solutions from primary data in order to break down the findings and to check if the research question has been correctly answered. In order to involve all the categories of respondents the questionnaires were randomly sent out and wasnt for just a particular group. With this method the researcher will be able to gather information required for the research aim, and the research findings will be well analysed. The total of questionnaires that were distributed was 80 and 68 was returned, electronic banking users were 72% while non electronic banking was 28%. Regardless of the little number of that responded, due to response, the rates of questionnaires are usually below 40% and results should still be broadly acceptable stated by (Cano, 2008) which has guide the researcher to resolve that a 30% response rate would be regarded valid for this research and results purpose. 4.2 Questionnaire A For easier and more detailed analysis of the information gathered, the results of questionnaires were put into charts and graph. According to Nachmias and Guerrero (2006, p.329) using a chart from the results gives way for simpler explanation for understanding. 4.2.1 Questionnaire Results Question 1: What is your Gender? Male = 43 responses Female = 25 responses In figure 4.1 the chart below shows the average of male and female respondents. The male respondents were averaged up to 65% while the female respondents were 35%. This indicates the increase of male users of electronic banking is more than the female users. Figure 4.1 Male and Female Respondents. Question 2: What age category do you fall into? 18 30 = 28 responses 31 40 = 21 responses 41 50 = 12 responses 51 64 = 7 responses 65 and Above = None In figure 4.2 the graph below, is the representation of age respondents who brought back questionnaires, 42% falls under the ages of 18 30 years, 32% falls under 31 40 years and another 18% was 41 50 years while ages 51 64 was 8% but they was no feedback on the 65 and above. Research made shows that ages 65 and above fall under the retirement stage or age and majority of them do not comprehend the utility of new technologies. However, Matilia Pento (2002) indicates the majority of electronic banking users are comparatively young and have been educated to use computers and the internet. This also shows that electronic banking in the society is mainly members of the working class. Figure 4.2 Age Category of Respondents. Question 3: What your level of education? O Levels = 9 responses BSc = 31 responses OND = 4 responses HND = 15 responses MBA = 9 responses In figure 4.3 this chart below shows the different respondents educational level is shown. 50% are University graduates (Bsc) holders, 20% are higher national diploma (HND) holders while master business administration (MBA) and O level holders shares the same average with 12% each. This shows that electronic banking users are educated. Sathye (1999, p.326) aver that people using electronic banking are well and highly educated. Figure 4.3 Educational Levels of Respondents. Question 4: What is your occupation? Accountants = 11 responses Doctors = 8 responses Engineers = 11 responses Lawyers = 4 responses Others = 20 responses Students = 11 responses Teachers = 4 responses In figure 4.4 the chart below is a representation of different respondents occupation from questionnaires that were returned. Accountants, Students and engineers share the same percentage with 16% each, Lawyers and Teachers also share the same percentage with 8.5% each, Doctors were 10 % and for respondents with other occupations which are not listed like farmers, traders and so on were 25%. Figure 4.4 Occupations of Respondents. Question 5: Do you have internet experience? Yes = 52 responses No = 17 responses In figure 4.5 the chart below represents the average of respondents that has experience with the internet which is 85% while the average of respondents without internet experience is 15% which makes a huge difference between them. Figure 4.5 Respondents With Internet Experience. Question 6: Do you have internet access? Yes = 45 responses No = 23 responsses In figure 4.6 the chart below is the representation of the total average of respondents that gave on questionnaires. In this chart 72% agreed and said yes to have access to the internet while 28% said NO they dont have access to the internet. Figure 4.6 Respondents With Internet Access. Question 7: How frequently do you use the internet? Often/Daily = 24 responses Few times a week = 19 responses Once in 2 weeks = 11 responses Once in 4 weeks = 8 responses Once in 6 weeks = 6 responses Once in 2months = 2 responses In figure 4.7 the frequency of internet usage is shown in the chart below. 35% of respondents use the internet often/daily, many respondents which average to 40.5% use the internet a couple of times a week, 10.5% use the internet once in two weeks, 8% use the internet once in a 4weeks, 4% use the internet once in 6 weeks, while 2% use the internet once every 2months. With research on respondents that are under categories 40.5% and 35% were people who have full-time office jobs and have internet access in their workplace and some who could afford internet in their homes. Figure 4.7 Frequencies of Internet Users. Question 8: Are you aware of electronic banking? Yes = 59 responses No = 9 responses In figure 4.8 the chart below the average of respondents aware of electronic banking are shown. 92% of the average represents those aware of electronic banking while 8% were not aware of electronic banking. Figure 4.8 Awareness of E-Banking of Respondents. Question 9: Do you have experience with any electronic banking service? Yes = 49 responses No = 19 responses In figure 4.9 the average of respondents that use electronic banking. 74% of respondents said yes for using one form of electronic banking or the other, and 26% of respondents said no. Nevertheless 25% out of the 74% respondents said they dont know the type of electronic banking they use, and they were added to the 74% because the answer yes on question on if they have used any form of electronic banking service. Figure 4.9 Respondents That Have Experience With E-Banking. Question 10: Which type of electronic banking service do you use? Online Banking = 14 responses ATM = 32 responses Telephone banking = 11 responses Post banking = 7 responses Branch banking = 4 responses In figure 4.10 this chart shows the total average of respondents using any form of electronic banking. The Automated Teller Machine (ATM) has the highest amount of respondents with 60%. The ATM is virtually the most utilized source of electronic banking for the respondents. The ATM is a single machine that has several features such as check onscreen balance, pays cash, prints account statement and so on. The ATM is widely known and is the most popular electronic banking source and the reason for this is that its easy to use and its convenience for accessing your account anywhere 24 hours a day 7 days a week without stepping into the bank. 17% of respondents uses online banking and another 15% of respondents use telephone banking. These two sources of electronic ba king are mainly used by business people or companies for transaction, direct debit and so on. 3% of respondents also use post banking and 5% use branch banking. Figure 4.10 E-Banking Preferred Options By Respondents. Question 11: How frequently do you use electronic banking services? Often/Daily = 32 responses Few times a week = 20 responses Once in 3 weeks = 10 responses Once in 6 weeks = 8 responses Once in 2months = 6 responses In figure 4.11 this chart shows the frequency of electronic banking usage is shown below. 54% use e-banking service very often, 24% of respondents use e-banking service once a week, 15% use electronic banking once in 3 weeks, 4.5% use the service once in 6 weeks while 2.5% use electronic banking service once in 2 months. This shows that users are increasingly adapting to the style of electronic banking. Figure 4.11 E-Banking Usages of Respondents. 4.2.2 Summary The survey results have actually shown the level of internet experience and the accessibility to internet by customers/clients. The customers/clients awareness of electronic banking was also shown; it could be viewed by the average of respondents using some of the electronic banking system such as Automated Teller Machine, Online banking and Telephone banking. With the automated teller machines (ATMs) having up to 60% of electronic banking awareness simply means its the most commonly used service. The ATM is easy to use and could be accessible anywhere 24 hours a day 7 days a week. Nevertheless a significant amount of respondents dont know the kind of electronic banking service they use; shown in the questionnaires that was returned. So therefore it is the banks responsibility to educate customers/client on these electronic banking services and their benefits. 4.3 Questionnaire B In this part questions are being directed to the banks to measure the kinds of electronic banking services they offer, and what they benefit from the services. Also, for any advertisement to attract new customers and to improve customer satisfaction. The two banks that were interviewed had one form of electronic banking system or the other. Both banks are being categorized into two different classes, old generation bank and new generation bank. The table below shows both banks that were interviewed and the electronic banking services they render, and they are into Mobile or Telephone banking service, Automated Teller Machine (ATM) service, Branch banking service and Online banking service. Nevertheless, both banks are not into Post banking service. One of the questions asked is if electronic banking has improved their place in the banking world and both banks replied with the same answer yes, that means the help of electronic banking has increased their in the industry and has g iven them the edge over competitors that have not yet applied these new technologies. However, the satisfactory level for customers has also increased and one of the reasons for that is because customers now have 24 hours access. The banks themselves has also benefited from the introduction of electronic banking in the sense that it has been helpful to reduce cost and man power. Research results from the banks that were interviewed shows that the banks has invested so much on security for the safety of customers to protect them from electronic theft. So therefore the installation security softwares has given banks the opportunity to protect customers personal information and to gain trust from their customers. Another question asked was if they have any advertising or improvement plans on electronic banking services, and both banks said yes to the question and are making plans for introducing internet access with a mobile phone and advertising it in public places such as shopping malls, post office and fuel stations for the improvement of electronic banking to catch the attention for new customers. Then the last question asked was how much is their estimated yearly turnover since electronic banking was introduced. The table shows results in a clearer understanding. Names Of Banks Electronic banking services Electronic banking services provided Has it Enhance Position Reduction of operational Cost Improved Customers Satisfaction Software in Used Plans for improvement Turn over Union Bank PLC Yes Online banking, telephone banking, ATM and Branch banking Yes Yes Yes Transactional code Internet access with mobile phone 93.7b Guarantee Trust Bank Yes Online banking, telephone banking, ATM and Branch banking Yes Yes Yes Transactional code Internet access with mobile phone 91.2b 4.4 Secondary Data Analysis In this section the focus is on two various research survey carried out by some Nigerian institutions. After analyzing this research, it will be utilized in results comparison from primary research. Franfort (2006, p.206) suggests more credibility will be gain on research finding if it comes out in number of reports and when collected data is analyzed in different times. It can also be utilized to explain and describe change. Nevertheless, some specific research purpose was not met by researcher in the survey from early research. Instead, it is more focused on the adoption of electronic banking and providing the use of electronic payment services in Nigeria. This is seen in the secondary research as a major limitation, regardless of this limitation the use of secondary research was utilized as a technical compliment review of literature and primary research for the aim of verifying and testing results. These permit researchers to make conclusive findings. 4.4.1 Research Survey 1 4.4.1.1 Background The adoption of electronic banking in Nigeria was the name of the title of this research which was handled by chiemeke in 2006, a Nigerian senior lecturer of computer science department in the University of Benin Nigeria. The aim of this research is to measure the stage of electronic banking services rendered by banks after deregulating the banking society and component that affects its adoption. The method used in the survey has a similarity with Diniz, (1998) model for evaluating status of the banks websites for transaction channels, Information delivery, Security level and customer relationship. 4.4.1.2 Results from Finding The research result on electronic banking services reveals that it has been rendered from the basic level of fundamental interaction. In the evaluation, out of 12 points score the results was between 4.5 and 11 points which means the basic level were high. However, as the interactivity level increases the scores reduces. Likewise, the outcome of functionality which was between 4 and 9.5 out of a total of 12 points, which indicate all banks do have information sites. Nevertheless, they were low scores on the transactional level of functionality which was between the range of 0.5 and 4.5. These indicate that electronic banking services rendered were on a low level. In addition, the score for the security level were also low with 47.7 percent adopted security level. However, some other known facts affecting electronic banking in Nigeria were poor power supply and unsatisfactory operational infrastructure. The aim of the research was at the banks and the adoption of electronic banki ng services rendered such as customer relationship, Transaction channels, Security level and information delivery and with the customers level of awareness of online banking service had no attention. The research questions of researchers were not answered, but nevertheless the transaction level of functionality questions were partly answered on the research question. This reason is probably because the two banks questioned are already offering one form of electronic banking service or the other. 4.4.2 Research Survey 2 4.4.2.1 Background The title of this research was called Telephone banking services and electronic payment system in Nigeria. Agboola conducted this research in 2006, another Nigerian senior lecturer in the Obafemi Awolowo University Nigeria. The evaluation of Telephone banking service and electronic payment system offered and used by Nigerian banks was the aim of this research. The method used on the research was the distribution of questionnaires and interview of banks personnel. As at that time chosen sample size was 36 banks out of the 89 banks. 4.4.2.2 Result from Findings The adoption rate of e-payment services results from analysis revealed that the most adopted technology is the Local Area Network (LAN) out of the 36 banks interviewed 35 banks adopted it. Likewise, out of the 36 banks interviewed 34 banks have adopted MICR cheques and already put to full use. Nevertheless, some technologies had low adoption rates. Telephone banking was one for them with a low adoption rate of 22%, the adoption rate for Automated Teller Machine (ATM) was 16.7% while the Home and office e-banking was 19.4%. This research supports the Chiemeka (2006) finding of inadequate power supply and poor operational infrastructure. Consequently, the focus of this research was on electronic payment devices used by banks and not on the awareness level of customers or e-banking adoption. However, to some extent the research question was answered, this observation could be seen from results with the adoption rate on telephone banking and 22% and the ATM having 16.7%. this shows that the banks are gradually adopting to these services. 4.4.3 Summary Identification of some form e-banking supporting the primary research has been identified by both research surveys. This clearly indicates the gradual process of customers adoption to these services and e-banking is been offered by the banks to some extent. RESEARCH FINDINGS 5.1 INTRODUCTION In this chapter, conclusions will be drawn on research findings and analysis from previous chapters will serve as a review mechanism for the aims and objectives of this project. 5.2 RESEARCH FINDINGS The non adoptions of electronic banking were the key elements that were discussed from the review of associated literatures. In previous research, indications showing the huge impediment to non adoption of electronic banking were lack of awareness and security. Meanwhile electronic banking from retail banks point of view is seen as a competitive advantage retaining their customers and the banks will greatly depend on their new technology adoption in the banking sector and with the advancement of technologies they can compete and be ahead of their competitors, this clearly means adoption electronic banking services has greater advantages over its disadvantages. The aims of the research were to analyse the level of customers awareness to electronic banking services and the rate of adoption of electronic banking service by Nigerian banks. Results from survey shows that electronic banking services are already in use by the two banks that were interviewed but both banks were not into post banking and the two banks are also introducing internet access with a mobile phone and advertising it in public places such as shopping malls, post office and fuel stations for the improvement of electronic banking to have a competitive advantage in the market, to retain existing customers and to catch the attention for new customers. However, the adoption of electronic banking and the level of awareness from customer shows 72% of respondents have access to internet while 28% do not have access to the internet. The level of internet experience and frequent use of computers in their workplace allows accessibility to the internet by customers/clients. On electronic banking level of awareness and the usage of its services, the percentage of respondents that are aware of electronic banking 92% and just 8% were not aware, and with another large 74% claim they are electronic banking users while 26% do not make use of electronic banking, and to a surprise 25% out of the 74% do not even know the type of electronic banking service they are using and this was because the electronic banking services listed on the questionnaire were not known as types of electronic banking by these respondents which still falls back to customers lack of awareness. Consequently, the Automated Teller Machine (ATM) has up to 60% adoption according to questionnaire results on the types on of electronic banking services being used, the ATM is easy to use, has 24 hours access and very convenient it is also said to have met customers needs. This research findings has endorsed (Agboola, 2006) on adopting automated payment systems gradually and less use of cash. Likewise, an interesting point noticed from the questionnaire results is the difference between male and female users using electronic banking services. These results shows that they are more male users using electronic services than the female with 65% male respondent s using these to 35% female, and this is because more male find the interest of going to the cyber cafà © and using the internet and by using the internet they get to actually know more about electronic banking services. However, questionnaire results for the educational level and age range of respondents shows that between ages 21 30 and 31 40 are highly educated and use the internet frequently, and their educational level in the questionnaire results, research findings indicates that users using electronic banking are educated and young. (Pento, 2002) findings indicate that users of electronic banking are well educated and have good experience using the internet, and most of them have access to the internet in their place of work and for those that can afford it get it have it in their homes. And a major barrier still affecting the adoption of electronic in Nigeria is still illiteracy according to (Ovia, 2001). From the secondary data findings of the research shows that the banks elementary stage has low adoption rate of electronic payment systems, banks should have informative websites rather than Transactional websites. However, primary research findings indicates that the bank interview all have electronic banking services rendered and have also laid down plans on how to improve electronic banking services in the future and obviously from the research results the banks and customers has made progressive acceptance on electronic banking services. 5.3 SUMMARY On research findings from the above discussion, it ought to have been seen that the introduction of electronic banking by banks has given them the opportunity to gain competitive advantage to attract new customers and to retain old ones and also to take up technical challenges. However, it is important that the banks educate their customers on the benefits and importance electronic banking could bring and to always upgrade their websites to be transactional and also to make their operational infrastructure get better. But if they dont the banks have the problem of customers low adoption will remain. In conclusion, some issues have to be addressed for the future of electronic banking in developing countries such as Nigeria, is the creation of awareness, security and constraints like poor infrastructure. Consequently, if these issues are addressed more customers will adopt electronic banking and the Nigerian banks would be able to gain global presence. Results from reviewing liter ature on electronic banking shows its jussive mood to investigate, the customers level of adoption in Nigeria and suggests key solutions to the constraints affecting electronic banking in Nigeria. All the same electronic banking has come to stay and has been well appreciated in the world and has given developing countries a future in the global economy.

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Human breast is a glandular organ comprising of lobular organization. A breast lobe has a lone lactiferous duct which branches in various segmental ducts with thousands of terminal ducts and lobules and ultimately opening at the nipple. Within the breast, the epithelial structure conquers a pyramid-like tissue space with the nipple at its tip and a broad base. As human breast is a pair, the lobes are recognized as individual units without any connections between them. It has been observed that the number of lobes, in a women’s lifetimes, remains constant even though the size varies based on progressive and regressive process that involving the role of age and hormonal status . In the second trimester of the embryonic development the primary ectoderm produces a bud like out growth known as the primordium nipple. During 21st-25th week of gestation, secondary buds develop into the underneath mesenchyme and slowly forms the breast166. But breasts continue to develop during fetal l ife with formation of fresh projections and the exhibit duel-cell architecture. The central cells express cytokeratins (CKs) 14 and 19 while the peripheral ones express CK19 only . As a human infant undergoes development after birth, the breast undergoes involution post influences of maternal hormones. During puberty, stromal elements undergo growth and ramification of ductal tree and lobe formation enlarges the breast167. Based on menstrual cycle, the female breast undergoes cyclical changes during

Team Discussion on App for Apple iPhone Free Essays

Working for Apple the type of research one would want to see done would be a reporting study. This type of study will display data that provides statistics comparing the application to other applications that users are already using and what features of the application users are wanting. This report is the first step in determining if the application is worth moving forward with. We will write a custom essay sample on Team Discussion on App for Apple iPhone or any similar topic only for you Order Now Once the application shows to be a valuable asset for users the next step is to focus on what the users want in an applications. I would expect the proposal to demonstrate on how user-friendly the application is, and who is the target audience this application is intended for. Many users want an application easy to use that a child can figure it out in one step. Another key factor users look for is the cost of the application. Keeping the cost down at a low price that is appealing to the user but profitable to the company will make this application successful for both parties. Derek’s Response to Nancy I think the reporting study would be a great way to determine whether or not to move forward with the acceptance of the App into the Apple Store. This is because the reporting study would give background information on the App study, including concrete details of the App and how it differs from other Apps in the same category. It would also give the necessary data to determine what group the App would best suit. This information would be obviously important because one would not want an App that is geared toward adults be in the viewing control of children without the proper warning labels. I think that it would have been a great way to find out if the customers would want to buy an app or not. When people are getting ready to get an app they definitely want something that is useful and they will not be disappointed with. When doing research you will be able to see if the app will do good or not. Also it will be able to decipher whether you are gearing it toward the correct audience. You do not want to just throw something out there to see if it will work without research. It is important to test your product before delivering it. If I worked for Apple, the first thing I would want to see in a proposal for a new App for the App store would be whether or not the proposal has met the policy and procedures by Apple. The reason I would do this is that if the requirements were met the App would be compatible with the requirements of Apple’s App store on so many levels. For example: If there are technical glitches or errors the App will not be approved by our technicians. I will also look for the simplicity of the App to make sure it will be user friendly. Creativity would play a big role in App approval because with more than 300,000 Apps in the App store, we would think it is important for the App to be unique. Research would be just as important as policies and procedures to gain approval for the App store. Although at times because of inappropriate research, we would have to be aware of this type of research to make sure it does not become part of the Apple App store. Inappropriate research will include anything that has any racial tones that may offend any of our customers and research must be in compliance with the law. Bottom line is, I will not except anything is unethical. User-friendly application is a function that users look for when deciding on purchasing the application or not. Statics stating what functions users are most likely to be attractive to provides insight if the product will be successful. These statics are important and presenting them in the proposal will help for determination of releasing the application. The application uniqueness is also important and knowing the competition of other application provides insight. Researching applications similar to the one in the proposal will reflect on the popularity of the new application. Following policies, procedures, compatibility, and ethical conduct are very important steps in business, but I am not sure if this information is appropriate research for a proposal. I agree with Derek on this one. You have to make sure that you can get approval from the app store before you try to finalize your product. If you were to introduce a product that was not something that the App store would not even be allowed to have in there store then you would be just wasting time. Research is the key ingredient to making sure that you are producing the right type of app or anything else. Without this we would have a lot of failed businesses. Always make sure that what we are producing is what the people want. Developers are constantly inventing and improving apps for the Apple ® iPhone ® mobile digital device. As a representative for Apple, researching the market of available apps helps take the first step into developing a successful app. A new app proposal requires a content analysis that helps educate developers on successful app designsand marketing. Proving there is a consumer interest for the app from a variety of age groups, demographics, genders, and geographical locations may help determine whether or not the app gets approved. The proposal should provide evidence regarding how the potential app meets the needs of Apple’s customer base. The proposed app plans should surpass the competition by demonstrating that it is one of a kind and has potential room for growth. The research of the app should determine its reliability and show data that ensure the app functions properly with the operating systems (OS) configurations for each device Apple offers. There are numerous apps with an exceedingly crowded market that the barrier to access is low and the barrier to attaining success is high. Offering research for an app that is difficult to duplicate but easy for customers to download will help in the approval process. However, including inappropriate research in the proposal is cause for disapproval. Technical problems like annoying bugs and constant crashes will result in disapproval from Apple. Using images, words, software, or ideas that Apple owns or information that does not pertain directly to the app and its functionality, technical content, or design criteria is inappropriate (Apple, 2012). Proposals containing explicit or offensive material such as adult material, racial slurs, and any kind of discrimination and defamation are considered inappropriate and disapproval may occur (Apple, 2012). However, there is also research that can be one of the priciest errors developers can make. Applying funds to insufficient research or researching ideas that are extensively available becomes futile for developers. They concentrate on generating original ideas and waste time as well as energy producing those apps. How to cite Team Discussion on App for Apple iPhone, Papers

Use of Machine Learning Program & Techniques-Samples for Students

Question: Discus about the Use of Machine learning program and techniques of data mining for speech to speech summarization of the text. Answer: Title: Investigation on the machine learning and data mining activities associated with the speech to speech and speech to text summarization. Introduction: In this paper we are going to research on the use of machine learning program and techniques of data mining for speech to speech summarization of the text. The speech recognition is the technologies which are used for converting the language spoken by the user into the text format by the computer. The voice recognition is the major component of the speech recognition methodology. It is the automatic recognition of the speech for mining of the text from the available data. It is the procedure followed for determining the relevant information and high quality data for the test available. The statistic pattern learning is the most useful techniques used for devising the trends in the accumulation of the high quality and accurate information. The summaries are presented by the speech methodology is categorised into two types which are classified as concatenation of the segmentation of the speech for extracting the unique speech presented and the second method synthesizing process used fo r summarization by making use of speech synthesizer. Research aim: The aim of the research is to implement the techniques of data mining for reducing the errors occurred in the compilation of the sentences. It helps in recognizing the procedures which are used for reducing the errors in the speech to speech program. Research questions and Objectives: The research questions which are undertaken for the completion of the research study are described below: How to avoid the wrong information due to errors in the speech recognition? Objective: To record the errors occurring in the speech recognition Policies used for minimizing the occurrence of errors in the speech recognition techniques The method used for removing the less important information before the compilation of the sentences. Proposal of different data mining techniques for the reduction of errors occurred in the sentence formation. Focusing on the advantage of data mining techniques in the recognition of less important data. Research hypothesis The performance of the existing system can be improved by indulging the speech recognition system in the working platform (Berry, 2014). The research hypothesis is constructed in developing the research study on the error occurred in process of speech recognition. The under-generation and the over-generation are used for creating the interpretation of the research hypothesis undertaken (Perner, 2010). H0: The rejection and acceptance of the error in the sentence construction helps in removing the errors from the phrases used. H1: The clarification of the request helps in confirmation of the concept for designing the error resistance model for the activities undertaken to establish error resistance working model for the summarization of the speech to speech and speech to text model (Cercone, 2012). H2: The concatenation of the speech segment for summarizing the scenario of sentences, words, and phrases helps in extracting the relevant information from it. H3: The errors are the deviation of the outcome from the expected results. H4: The word error rate is used for computing the errors are used for identifying the rate of insertion, deletion, and substitution. H5: The concept error rate is used for determining the quantity of errors occurred in the concatenation of the sentences (Dinoy, 2016). H6: The categorisation of the rigid parser helps in demonstrating the over generation and under generation of the resources. H7: The tendency of recalling the occurrences of the activities helps in managing the errors. The consequences help in determining the constraint ratio. Background and significance The communication plays a vital role in gaining accuracy in the working structure of the report generation and required documentation. The process of speech recognition was introduced in converting the spoken words into textual sentences (Moreno, 2012). The efficiency of converting the words into text can be improved and enhanced with the accumulation of the speech program. It has been analysed that the errors occurred in the preparation of the documentation through speech recognition system raises the dissatisfaction in the user because of the occurrence of errors in the development of the report. The turnaround time of producing the report is increased due to occurrence of errors. The substitution of the wrong word in the phrases can completely changed the meaning of the sentences. The focus should be given on the usage of the two stage protocol for constructing the sentence with accuracy. The effectiveness and efficiency can be improved of the sentence construction for managing the compression ratio of larger sentence to reduce the rate of error. The extraction of the sentence depends on the use of three scores which are categorised as Linguistic score, significance score, and confidence score. The error handling helps in demonstrating the errors in the scenari (Liu, 2006). The following table shows the types of errors which occurred in the given scenario of speech recognition techniques (Source: Kang, 2013). Dialogue strategies to overcome speech recognition errors inform filling dialogue) Categories Over generation error type Under generation error type Categorisation of the errors Low precision of errors Low recalling of the errors Occurrence of ASR errors Process of insertion Process of deletion Occurrence of miscommunication Occurrence of misunderstanding in the complete process of the concatenation of the sentences Non-understanding of the error prone construction of the sentences. Consequences of the error prone sentence Failure of the task Repetition of the occurrence of errors The identification of the errors helps in reducing the errors in the construction of the speech recognition system. The acoustic and language model is used for determining the constant error which occurred in the construction of the sentence. The speech recognition system is associated with the variable errors. The expectation of the outputs helps in developing the error resistance system which is capable of enlightening the clear understanding of the information transmitted by the speaker. The handling of error helps in resolving the issues associated with the understanding capability of the receiver and the sender. The false exception and rejection helps in optimising the reduction in the error rate. The correction and in-correction in the decision creates the problem for the speech recognition system. The detection and correction methods are used list of methods used for determining the sequence of activities. The command dialogue helps in establishing the n-list associated with the errors. The prediction of error helps in handling the classification of baseline for the improvement plan for continuous error deduction procedure used. The decision chart or deduction of the error works on four processes which are classified as acceptance, rejection, understanding of the display, and clarification of the request. The division of the problem helps in the identification of the error prone area. The theoretical model for predicting the data driven policies helps in analysing the ground decision. The error detection in the later phases helps in predicting the inconsistency for the re-evaluation of the assumptions taken in the development of the speech to speech summarization and speech to text summarization. The following table shows the positive and negatives cues of the speech recognition system which is undertaken for analysing the speech to speech and speech to text summarization. The handling of error can be done by the series of functions which are categorised as development of the new system, repetition of the processes undertaken by the user, integration of the system, modification of the user requirement, and the negation of the user. Research methodology The qualitative and quantitative research methodology has been undertaken on analysing the facts and figures associated with the investigation of the data mining techniques used in the formulation of the speech to speech and speech to text summarization. The interview is arranged with the IT experts to gather facts and figures which helps in analysing the investigation of the data mining techniques used in the formulation of the speech to speech and speech to text summarization. The scenario of interview is developed for formulating the solution for reducing the errors occurred in the system of speech synthesis. The questionnaire is arrange with many IT expert under the same platform for analysing the difference in the information provided by different expert on the program of data mining in the speech text summarization system. Focused groups is group of IT experts which are in collecting the relevant information based on real and virtual facts collected from the different sources o n the common platform (Najafabadi, 2012). Sampling method is based on the selection of the small sample for organizing the experiment for analysing the frequency of errors occurred in the construction of the sentence. The sampling methods help in analysing the defects and gaps which exist in the concatenation of the phrases for the development of the sentence (Kawle, 2013). The qualitative and quantitative methods are used for predicting the errors occurred in the spoken sentences. The data gathered from focused groups, interviews, and other qualitative approach helps in providing the details of using the following data mining techniques for reducing the errors in the sentence formation which are stated below: Unsupervised data mining techniques Semi-Supervised Data mining techniques Supervised data mining techniques Sentiment lexicon techniques Classification of the lexical sentiments Support vector machine Distinction of positive and negative binary data Transductive vector machine support Use of nave bayes Orientation of the sentiments Detection of the polarity Adaptation of the nave bayes Extraction of the patterns Mincuts of the randomised data Developments of the decision tree. The identification of the problematic error helps in devising the concept level clarification. The alternative clarification helps in generating parallel hypothesis for the management of the decision problem. The fixing of the errors helps in developing the robust processes for determining the uncertainty and ambiguity in the development of the speech recognition system. The following tasks should be taken under consideration while collecting data on the speech to speech synthesis. Tokenization process: The sequence of character is break down into tokens which can be used for putting punctuation marks in the text for further processing. The higher rte is generated with longer sentences. Filtering: Filtering is the process focuses on removing the extra word from the frequently appeared text. Lemmatization: It is used for doing the morphological analysis on the sequence of characters. Stemming: Stemming is the methodology used for obtaining the root words from the sequence of derived words. Research Philosophy: Research philosophy focuses on the use of knowledge for speech text summarization. The complexity with the investigating techniques is raised due to the potential risks associated with the deployment of speech recognition system. The accuracy is the major factor associated with the preparation of the report through the speech to speech recognition system or speech to text recognition system. The ontological research philosophy is used for defining the process of conceptualization between different terms for finding out the relationship between the knowledge based recognized domains. Research Strategy: The focus should be given on the sources which are responsible for the occurrence of uncertainty and the errors in human, age, gender, and variability in the dialects used for the construction of the sentence for communication between the participating units. The speaking rate is the major factor responsible for the occurrence of errors. The unpredictable results helps in establishing the errors related with the out of vocabulary. The errors can be handled with the distinguishing of bugs and exceptions which occurred in the speech recognition system. Research Design: The research design focuses on analysing the research problem and correlation between dependent and independent variable for analysing the speech text summarization. The system is comprised with the robust assessment of the hypothetical activities for resolving the occurrence of error occurred in the complete scenario for the construction and concatenation of the sentences (Neto, 2015). The acceptance of the concept helps in defining the error resistance background for the construction of the sentence. Data Collection: The following are the data collection methods used for collecting data for the speech text summarization process: Nave Bayes Collection Method: This is the approach which is based on assumptions. Bayes rules is used for collecting the parameters for the study. The independency is the common rule which is used for the different data collected. The calculation of the probabilities can be done by summing the probabilities for the variety of components (Sources: Nenkova, A. (2016). A survey of text summarization techniqies. 1st ed. [ebook]). The highest probability can be calculated by the following: Nearest Neighbour collection method: This method is used for measuring distance based data to improve the classification methodology. The k-nearest neighbour is used for the classification of different components. Decision Tree collection method: This methodology is used for calculating the value of the attributes in the given hierarchy of data. The root node is classified as the instance for the tree structure. Support Vector Machine: This is used for supervising the liner classifiers which helps in taking the decision based on the linear combination of the data. It helps in providing the robust data of high dimension. Data analysis: Analysis of the Speech text summarization: The speech text summarization depends on the sequence of two stages which are categorised as extraction of the sentence and compaction of the sentence. The result helps in calculating the accuracy of the sentence. The filers are removed from the sentence for controlling the automatic speech system. The following diagram shows the automation system which is used for text summarization ( Source: Zhong, N. (2012). Effective pattern discovery for text mining. 1st ed. [ebook]). Procedure of sentence extraction: The following equation is used for storing the result of the automatic speech summarization system. Here, N represent the number of words used in representing the construction of the sentence, L(wi) represent the linguistic score of the sentence, I(wi) represent the significance score, and C(wi) represent the confidence score of the sentence (W). These scores help in the representation of the compaction method. Compaction of the sentence: The low significant sentences are removed for achieving accuracy by reducing the number of errors. The transcription procedures are used for calculating the sentence compaction score. The three scores are used for managing transcription of the word (Govindraj, 2016). The dependency of the phrases can be improved by providing structured format to the grammar used in the construction of the sentences (Chakraborty, 2014). The concatenation score is used for measuring the compression ratio with the use of protocol named as 2-stage dynamic protocol. The fillers are used for managing the difference between the participating units. The rejection and acceptance of the error in the sentence construction helps in removing the errors from the phrases used (Bramer, 2013). The clarification of the request helps in confirmation of the concept for designing the error resistance model for the activities undertaken to establish error resistance working model for the summarization of the speech to spe ech and speech to text model (Furui, 2013)). This protocol helps in developing the compression ratio according to the demand of the sentence formation to achieve accuracy and minimizing errors in the sentence. The accuracy in the summarization can be achieved by using transcription process in the evaluation of the set target. The variation in the speech summarization theory helps in constructing the sentence with accuracy (Zhong, 2012). The following string shows the example of sentence formation with the use of speech recognition technique with accuracy (Source: Zhong, 2012. Effective pattern discovery for text mining. 1st ed. [ebook]). The two stage protocol depends on the random selection of the word, the weighting factor, optimization of the value used, and recurrence in the summary word, linguistic score, confidence score, and significance score. Analysis of the Speech to speech presentation and summarization: The concatenation of the speech segment for summarizing the scenario of sentences, words, and phrases helps in extracting the relevant information from it. The importance should be given on extracting criteria. The summary speech is used for managing the concatenation methods (Antino, 2012). The investigation helps in managing the relationship between words, sentences, and fillers. The reliability of the method can be achieved by managing the occurrence of spontaneous speech. The correction is recognized automatically for extracting the speech segmentation (Chakraborty, 2010). The purpose of this paper is to reduced errors from the construction of the sentence. The important sentence depends on the synchronization of the result achieved. The removal of the unwanted words helps in reducing the length of the sentence and reducing errors (Gonzalez, 2015). The filler units are used for managing the boundaries of the sentence for extracting expected results. The intermediate results can be developed with the use of continuity of acoustic speech. The evaluation of the units depends on the recognition of the consequences associated with the speech extraction. Concatenation of the participating units: The segmentation boundaries help in attaining the required results for obtaining amplitude difference for the waveform formation for analysing the accuracy for the deployment of result. The speaking rate helps in managing the unnatural sound held in the short pause of the sentence. It has been analysed that the length of the speaking rate should be in between 50 and 100 ms (Kang, 2013). The summarization of the sentence helps in increasing the data transfer rate for enhancing the frequency of conversion. The speech period is the time for which text sentences are summarised to give accuracy and relevancy in the result. The text sentences are used for managing the time required for the concatenation of the sentences. The upgrading of the short pause ad long pause helps in demonstrating the speech waveforms for managing the boundaries of the sentences. The attenuation is inserted in the sentences for reducing the rate of errors in the construction of the sentences through the medium of speech recognition system. The insertion of the long pauses helps in identifying the completion of the sentence (Bijuraj, 2013). The concatenation of the word limit helps in analysing the termination of the sentences. Time Line Activity chart of the research study Timeline for starting the research Timeline for completing the research Description of the activities performed Research undertaken 09-Oct-17 10-Oct-17 The research is undertaken on the topic Investigation on the machine learning and data mining activities associated with the speech to speech and speech to text summarization Selection of team criteria 11-Oct-17 13-Oct-17 The experienced and the expertise person should be selected for carrying out the research activities in gathering relevant data for the research study Collection of data required for carrying out the process of literature review 14-Oct-17 16-Oct-17 The format should be developed for collecting required data to carry out the research studies. Tools and techniques used for data analysis 17-Oct-17 19-Oct-17 The study of the literature helps in analysing the required data selection needed for the designing of the research study Construction of research questions according to the research undertaken 20-Oct-17 23-Oct-17 The designing of the research question is the vital role in the preparation of the research study because the data collected from different sources are depends on the primary and secondary research questions prepared for the completion of the research study Drafting a research proposal 24-Oct-17 26-Oct-17 The designing of the draft is based on the research questions designed on the investigation of speech to speech summarization with the use of machine learning program Deployment of research methodologies 27-Oct-17 20-Nov-17 The relevant and adequate data can be collected with the use of research methodologies such as face to face interview, questionnaire, focused group, observation, and others Reviewing of the draft prepared for research undertaken 21-Nov-17 23-Nov-17 Reviewing of the draft prepared for research undertaken Providing the research draft for sanctioning and approval 24-Nov-17 27-Nov-17 The research authority approved the research proposal on the investigation of speech to speech summarization with the use of machine learning program (Garla, 2010) Analysis of the research documentation collected 28-Nov-17 30-Dec-17 The data analysis of tools and technologies are used for investigation of speech to speech summarization with the use of machine learning program Findings and assessment 01-Jan-18 10-Jan-18 The focus should be given on the clear understanding on investigation of speech to speech summarization with the use of machine learning program Completion of the undertaken research 11-Jan-18 20-Jan-18 Submission of the research undertaken on the topic Investigation on the machine learning and data mining activities associated with the speech to speech and speech to text summarization Budget The budget allocated for conducting the research study is around $ 6000 on investigation of speech to speech data mining techniques. $ 1200 is allocated for conducting the literature review and collecting data from research methodologies. $ 1200 is used for data collection and data analysis for finding the result of the undertaken research. $ 2500 is spent on traveling allowance. $ 1100 are used for conducting experiments for the analysis of the error occurred in the process of data mining in the speech to speech summarization. The following table shows the distribution of the budget allocated to the research study. Activities Allocated budget literature review and collecting data from research methodologies $ 1200 Data collection and data analysis for finding the result of the undertaken research $ 1200 Traveling allowance $ 1500 Conducting experiments for the analysis of the error occurred in the process of data mining in the speech to speech summarization $ 1100 Development of the research report $ 1000 Total estimated cost $ 6000 Research limitation The limitation of the research is the number of samples used for study. The sub-analysis of the finding has not been done (Nenkova, 2016). The proposed budget and time is inefficient in handling the research proposal. Constraints: The major constraints associated with the speech text summarization are the concatenation of the words and the construction of the sentence. Ethical Issues: The miscommunication is the major problem which can give birth to the misunderstanding. The interpretation of the speaker language is wrongly done by the receiving units which creates the scenario of the misunderstanding. The intention and the emotion of the listener are misinterpreted by the receiver. Conclusion The purpose of this paper is to reduced errors from the construction of the sentence. The important sentence depends on the synchronization of the result achieved. The removal of the unwanted words helps in reducing the length of the sentence and reducing errors. The two phased protocol developing the compression ratio according to the demand of the sentence formation to achieve accuracy and minimizing errors in the sentence. The reliability of the method can be achieved by managing the occurrence of spontaneous speech. The errors is the deviation of the outcome from the expected results. The errors are categorised into two categories which are under generation and over generation. The insertion and deletion process is used for handling the errors in the construction of the sentence. The correction is recognized automatically for extracting the speech segmentation. The clarification of the request helps in confirmation of the concept for designing the error resistance model for the a ctivities undertaken to establish error resistance working model for the summarization of the speech to speech and speech to text model. The attenuation is inserted in the sentences for reducing the rat of errors in the construction of the sentences through the medium of speech recognition system. The effectiveness and efficiency can be improved of the sentence construction for managing the compression ratio of larger sentence to reduce the rate of error. References: Antino, H. (2012). Emerging technologies of text mining: Techniques and applications. 1st ed. [ebook]. [Accessed 06 Oct. 2017]. Berry, M. (2014). Survey of text mining: clustering, classification, and retrieval. 1st ed. [ebook]. [Accessed 06 Oct. 2017]. Bijuraj, L. (2013). Clustering and its applications. 1st ed. [ebook]. [Accessed 06 Oct. 2017]. Bramer, M. (2013). Research and development in intelligent system. 1st ed. [ebook]. [Accessed 06 Oct. 2017]. Cercone, N. (2012).Advances in knowledge discovery and data mining . 1st ed. [ebook]. [Accessed 06 Oct. 2017]. Chakraborty, G. (2014). Analysis of unstructured data: Application of text analytics and sentiment mining. [Accessed 06 Oct. 2017]. Dinoy, I. (2016). Methodological challenges and analytic opportunities for modelling and interpreting big data. 1st ed. [ebook]. [Accessed 06 Oct. 2017]. Furui, S. (2013). Speech to speech and speech to text summarization. 1st ed. [ebook]. [Accessed 06 Oct. 2017]. Garla, S. (2010). Text mining and analysis. 1st ed. [ebook]. [Accessed 06 Oct. 2017]. Gonzalez, G. (2015).Recent advances and emerging applications in text and data mining for biomedical discovery. [Accessed 06 Oct. 2017]. Govindraj, S. (2016). Intensified sentiments analysis of customers product review using acoustic and textual features. 1st ed. [ebook]. [Accessed 06 Oct. 2017]. Kang, S. (2013). Dialogue strategies to overcome speech recognition errors inform filling dialogue. [Accessed 06 Oct. 2017]. Kawle, A. (2013). Text to speech web plugin with text summarisation. 1st ed. [ebook]. [Accessed 06 Oct. 2017]. Koulali, R. (2011). Topic detection and multi-word terms extraction for Arabic unvowelized documents. 1st ed. [ebook]. [Accessed 06 Oct. 2017]. Liu, Y. (2006). A study on the machine learning from imbalanced data for sentence boundary detection in speech. 1st ed. [ebook]. [Accessed 06 Oct. 2017]. Moreno, A. (2012). Text analytics: The convergence of big data and artificial intelligence. 1st ed. [ebook]. [Accessed 06 Oct. 2017]. Najafabadi, M. (2012). Deep learning application and challenges in big data. 1st ed. [ebook]. [Accessed 06 Oct. 2017]. Nenkova, A. (2016). A survey of text summarization techniqies. 1st ed. [ebook]. [Accessed 06 Oct. 2017]. Neto, J. (2015). Automatic text summarization using a machine learning approach. 1st ed. [ebook]. [Accessed 06 Oct. 2017]. Perner, P. (2010). Machine learning and data mining in pattern recognition. 1st ed. [ebook]. [Accessed 06 Oct. 2017]. Solka, J. (2013). Text data mining theory and methods. 1st ed. [ebook]. [Accessed 06 Oct. 2017]. Zhong, N. (2012). Effective pattern discovery for text mining. 1st ed. [ebook]. [Accessed 06 Oct. 2017].

Use of Machine Learning Program & Techniques-Samples for Students

Question: Discus about the Use of Machine learning program and techniques of data mining for speech to speech summarization of the text. Answer: Title: Investigation on the machine learning and data mining activities associated with the speech to speech and speech to text summarization. Introduction: In this paper we are going to research on the use of machine learning program and techniques of data mining for speech to speech summarization of the text. The speech recognition is the technologies which are used for converting the language spoken by the user into the text format by the computer. The voice recognition is the major component of the speech recognition methodology. It is the automatic recognition of the speech for mining of the text from the available data. It is the procedure followed for determining the relevant information and high quality data for the test available. The statistic pattern learning is the most useful techniques used for devising the trends in the accumulation of the high quality and accurate information. The summaries are presented by the speech methodology is categorised into two types which are classified as concatenation of the segmentation of the speech for extracting the unique speech presented and the second method synthesizing process used fo r summarization by making use of speech synthesizer. Research aim: The aim of the research is to implement the techniques of data mining for reducing the errors occurred in the compilation of the sentences. It helps in recognizing the procedures which are used for reducing the errors in the speech to speech program. Research questions and Objectives: The research questions which are undertaken for the completion of the research study are described below: How to avoid the wrong information due to errors in the speech recognition? Objective: To record the errors occurring in the speech recognition Policies used for minimizing the occurrence of errors in the speech recognition techniques The method used for removing the less important information before the compilation of the sentences. Proposal of different data mining techniques for the reduction of errors occurred in the sentence formation. Focusing on the advantage of data mining techniques in the recognition of less important data. Research hypothesis The performance of the existing system can be improved by indulging the speech recognition system in the working platform (Berry, 2014). The research hypothesis is constructed in developing the research study on the error occurred in process of speech recognition. The under-generation and the over-generation are used for creating the interpretation of the research hypothesis undertaken (Perner, 2010). H0: The rejection and acceptance of the error in the sentence construction helps in removing the errors from the phrases used. H1: The clarification of the request helps in confirmation of the concept for designing the error resistance model for the activities undertaken to establish error resistance working model for the summarization of the speech to speech and speech to text model (Cercone, 2012). H2: The concatenation of the speech segment for summarizing the scenario of sentences, words, and phrases helps in extracting the relevant information from it. H3: The errors are the deviation of the outcome from the expected results. H4: The word error rate is used for computing the errors are used for identifying the rate of insertion, deletion, and substitution. H5: The concept error rate is used for determining the quantity of errors occurred in the concatenation of the sentences (Dinoy, 2016). H6: The categorisation of the rigid parser helps in demonstrating the over generation and under generation of the resources. H7: The tendency of recalling the occurrences of the activities helps in managing the errors. The consequences help in determining the constraint ratio. Background and significance The communication plays a vital role in gaining accuracy in the working structure of the report generation and required documentation. The process of speech recognition was introduced in converting the spoken words into textual sentences (Moreno, 2012). The efficiency of converting the words into text can be improved and enhanced with the accumulation of the speech program. It has been analysed that the errors occurred in the preparation of the documentation through speech recognition system raises the dissatisfaction in the user because of the occurrence of errors in the development of the report. The turnaround time of producing the report is increased due to occurrence of errors. The substitution of the wrong word in the phrases can completely changed the meaning of the sentences. The focus should be given on the usage of the two stage protocol for constructing the sentence with accuracy. The effectiveness and efficiency can be improved of the sentence construction for managing the compression ratio of larger sentence to reduce the rate of error. The extraction of the sentence depends on the use of three scores which are categorised as Linguistic score, significance score, and confidence score. The error handling helps in demonstrating the errors in the scenari (Liu, 2006). The following table shows the types of errors which occurred in the given scenario of speech recognition techniques (Source: Kang, 2013). Dialogue strategies to overcome speech recognition errors inform filling dialogue) Categories Over generation error type Under generation error type Categorisation of the errors Low precision of errors Low recalling of the errors Occurrence of ASR errors Process of insertion Process of deletion Occurrence of miscommunication Occurrence of misunderstanding in the complete process of the concatenation of the sentences Non-understanding of the error prone construction of the sentences. Consequences of the error prone sentence Failure of the task Repetition of the occurrence of errors The identification of the errors helps in reducing the errors in the construction of the speech recognition system. The acoustic and language model is used for determining the constant error which occurred in the construction of the sentence. The speech recognition system is associated with the variable errors. The expectation of the outputs helps in developing the error resistance system which is capable of enlightening the clear understanding of the information transmitted by the speaker. The handling of error helps in resolving the issues associated with the understanding capability of the receiver and the sender. The false exception and rejection helps in optimising the reduction in the error rate. The correction and in-correction in the decision creates the problem for the speech recognition system. The detection and correction methods are used list of methods used for determining the sequence of activities. The command dialogue helps in establishing the n-list associated with the errors. The prediction of error helps in handling the classification of baseline for the improvement plan for continuous error deduction procedure used. The decision chart or deduction of the error works on four processes which are classified as acceptance, rejection, understanding of the display, and clarification of the request. The division of the problem helps in the identification of the error prone area. The theoretical model for predicting the data driven policies helps in analysing the ground decision. The error detection in the later phases helps in predicting the inconsistency for the re-evaluation of the assumptions taken in the development of the speech to speech summarization and speech to text summarization. The following table shows the positive and negatives cues of the speech recognition system which is undertaken for analysing the speech to speech and speech to text summarization. The handling of error can be done by the series of functions which are categorised as development of the new system, repetition of the processes undertaken by the user, integration of the system, modification of the user requirement, and the negation of the user. Research methodology The qualitative and quantitative research methodology has been undertaken on analysing the facts and figures associated with the investigation of the data mining techniques used in the formulation of the speech to speech and speech to text summarization. The interview is arranged with the IT experts to gather facts and figures which helps in analysing the investigation of the data mining techniques used in the formulation of the speech to speech and speech to text summarization. The scenario of interview is developed for formulating the solution for reducing the errors occurred in the system of speech synthesis. The questionnaire is arrange with many IT expert under the same platform for analysing the difference in the information provided by different expert on the program of data mining in the speech text summarization system. Focused groups is group of IT experts which are in collecting the relevant information based on real and virtual facts collected from the different sources o n the common platform (Najafabadi, 2012). Sampling method is based on the selection of the small sample for organizing the experiment for analysing the frequency of errors occurred in the construction of the sentence. The sampling methods help in analysing the defects and gaps which exist in the concatenation of the phrases for the development of the sentence (Kawle, 2013). The qualitative and quantitative methods are used for predicting the errors occurred in the spoken sentences. The data gathered from focused groups, interviews, and other qualitative approach helps in providing the details of using the following data mining techniques for reducing the errors in the sentence formation which are stated below: Unsupervised data mining techniques Semi-Supervised Data mining techniques Supervised data mining techniques Sentiment lexicon techniques Classification of the lexical sentiments Support vector machine Distinction of positive and negative binary data Transductive vector machine support Use of nave bayes Orientation of the sentiments Detection of the polarity Adaptation of the nave bayes Extraction of the patterns Mincuts of the randomised data Developments of the decision tree. The identification of the problematic error helps in devising the concept level clarification. The alternative clarification helps in generating parallel hypothesis for the management of the decision problem. The fixing of the errors helps in developing the robust processes for determining the uncertainty and ambiguity in the development of the speech recognition system. The following tasks should be taken under consideration while collecting data on the speech to speech synthesis. Tokenization process: The sequence of character is break down into tokens which can be used for putting punctuation marks in the text for further processing. The higher rte is generated with longer sentences. Filtering: Filtering is the process focuses on removing the extra word from the frequently appeared text. Lemmatization: It is used for doing the morphological analysis on the sequence of characters. Stemming: Stemming is the methodology used for obtaining the root words from the sequence of derived words. Research Philosophy: Research philosophy focuses on the use of knowledge for speech text summarization. The complexity with the investigating techniques is raised due to the potential risks associated with the deployment of speech recognition system. The accuracy is the major factor associated with the preparation of the report through the speech to speech recognition system or speech to text recognition system. The ontological research philosophy is used for defining the process of conceptualization between different terms for finding out the relationship between the knowledge based recognized domains. Research Strategy: The focus should be given on the sources which are responsible for the occurrence of uncertainty and the errors in human, age, gender, and variability in the dialects used for the construction of the sentence for communication between the participating units. The speaking rate is the major factor responsible for the occurrence of errors. The unpredictable results helps in establishing the errors related with the out of vocabulary. The errors can be handled with the distinguishing of bugs and exceptions which occurred in the speech recognition system. Research Design: The research design focuses on analysing the research problem and correlation between dependent and independent variable for analysing the speech text summarization. The system is comprised with the robust assessment of the hypothetical activities for resolving the occurrence of error occurred in the complete scenario for the construction and concatenation of the sentences (Neto, 2015). The acceptance of the concept helps in defining the error resistance background for the construction of the sentence. Data Collection: The following are the data collection methods used for collecting data for the speech text summarization process: Nave Bayes Collection Method: This is the approach which is based on assumptions. Bayes rules is used for collecting the parameters for the study. The independency is the common rule which is used for the different data collected. The calculation of the probabilities can be done by summing the probabilities for the variety of components (Sources: Nenkova, A. (2016). A survey of text summarization techniqies. 1st ed. [ebook]). The highest probability can be calculated by the following: Nearest Neighbour collection method: This method is used for measuring distance based data to improve the classification methodology. The k-nearest neighbour is used for the classification of different components. Decision Tree collection method: This methodology is used for calculating the value of the attributes in the given hierarchy of data. The root node is classified as the instance for the tree structure. Support Vector Machine: This is used for supervising the liner classifiers which helps in taking the decision based on the linear combination of the data. It helps in providing the robust data of high dimension. Data analysis: Analysis of the Speech text summarization: The speech text summarization depends on the sequence of two stages which are categorised as extraction of the sentence and compaction of the sentence. The result helps in calculating the accuracy of the sentence. The filers are removed from the sentence for controlling the automatic speech system. The following diagram shows the automation system which is used for text summarization ( Source: Zhong, N. (2012). Effective pattern discovery for text mining. 1st ed. [ebook]). Procedure of sentence extraction: The following equation is used for storing the result of the automatic speech summarization system. Here, N represent the number of words used in representing the construction of the sentence, L(wi) represent the linguistic score of the sentence, I(wi) represent the significance score, and C(wi) represent the confidence score of the sentence (W). These scores help in the representation of the compaction method. Compaction of the sentence: The low significant sentences are removed for achieving accuracy by reducing the number of errors. The transcription procedures are used for calculating the sentence compaction score. The three scores are used for managing transcription of the word (Govindraj, 2016). The dependency of the phrases can be improved by providing structured format to the grammar used in the construction of the sentences (Chakraborty, 2014). The concatenation score is used for measuring the compression ratio with the use of protocol named as 2-stage dynamic protocol. The fillers are used for managing the difference between the participating units. The rejection and acceptance of the error in the sentence construction helps in removing the errors from the phrases used (Bramer, 2013). The clarification of the request helps in confirmation of the concept for designing the error resistance model for the activities undertaken to establish error resistance working model for the summarization of the speech to spe ech and speech to text model (Furui, 2013)). This protocol helps in developing the compression ratio according to the demand of the sentence formation to achieve accuracy and minimizing errors in the sentence. The accuracy in the summarization can be achieved by using transcription process in the evaluation of the set target. The variation in the speech summarization theory helps in constructing the sentence with accuracy (Zhong, 2012). The following string shows the example of sentence formation with the use of speech recognition technique with accuracy (Source: Zhong, 2012. Effective pattern discovery for text mining. 1st ed. [ebook]). The two stage protocol depends on the random selection of the word, the weighting factor, optimization of the value used, and recurrence in the summary word, linguistic score, confidence score, and significance score. Analysis of the Speech to speech presentation and summarization: The concatenation of the speech segment for summarizing the scenario of sentences, words, and phrases helps in extracting the relevant information from it. The importance should be given on extracting criteria. The summary speech is used for managing the concatenation methods (Antino, 2012). The investigation helps in managing the relationship between words, sentences, and fillers. The reliability of the method can be achieved by managing the occurrence of spontaneous speech. The correction is recognized automatically for extracting the speech segmentation (Chakraborty, 2010). The purpose of this paper is to reduced errors from the construction of the sentence. The important sentence depends on the synchronization of the result achieved. The removal of the unwanted words helps in reducing the length of the sentence and reducing errors (Gonzalez, 2015). The filler units are used for managing the boundaries of the sentence for extracting expected results. The intermediate results can be developed with the use of continuity of acoustic speech. The evaluation of the units depends on the recognition of the consequences associated with the speech extraction. Concatenation of the participating units: The segmentation boundaries help in attaining the required results for obtaining amplitude difference for the waveform formation for analysing the accuracy for the deployment of result. The speaking rate helps in managing the unnatural sound held in the short pause of the sentence. It has been analysed that the length of the speaking rate should be in between 50 and 100 ms (Kang, 2013). The summarization of the sentence helps in increasing the data transfer rate for enhancing the frequency of conversion. The speech period is the time for which text sentences are summarised to give accuracy and relevancy in the result. The text sentences are used for managing the time required for the concatenation of the sentences. The upgrading of the short pause ad long pause helps in demonstrating the speech waveforms for managing the boundaries of the sentences. The attenuation is inserted in the sentences for reducing the rate of errors in the construction of the sentences through the medium of speech recognition system. The insertion of the long pauses helps in identifying the completion of the sentence (Bijuraj, 2013). The concatenation of the word limit helps in analysing the termination of the sentences. Time Line Activity chart of the research study Timeline for starting the research Timeline for completing the research Description of the activities performed Research undertaken 09-Oct-17 10-Oct-17 The research is undertaken on the topic Investigation on the machine learning and data mining activities associated with the speech to speech and speech to text summarization Selection of team criteria 11-Oct-17 13-Oct-17 The experienced and the expertise person should be selected for carrying out the research activities in gathering relevant data for the research study Collection of data required for carrying out the process of literature review 14-Oct-17 16-Oct-17 The format should be developed for collecting required data to carry out the research studies. Tools and techniques used for data analysis 17-Oct-17 19-Oct-17 The study of the literature helps in analysing the required data selection needed for the designing of the research study Construction of research questions according to the research undertaken 20-Oct-17 23-Oct-17 The designing of the research question is the vital role in the preparation of the research study because the data collected from different sources are depends on the primary and secondary research questions prepared for the completion of the research study Drafting a research proposal 24-Oct-17 26-Oct-17 The designing of the draft is based on the research questions designed on the investigation of speech to speech summarization with the use of machine learning program Deployment of research methodologies 27-Oct-17 20-Nov-17 The relevant and adequate data can be collected with the use of research methodologies such as face to face interview, questionnaire, focused group, observation, and others Reviewing of the draft prepared for research undertaken 21-Nov-17 23-Nov-17 Reviewing of the draft prepared for research undertaken Providing the research draft for sanctioning and approval 24-Nov-17 27-Nov-17 The research authority approved the research proposal on the investigation of speech to speech summarization with the use of machine learning program (Garla, 2010) Analysis of the research documentation collected 28-Nov-17 30-Dec-17 The data analysis of tools and technologies are used for investigation of speech to speech summarization with the use of machine learning program Findings and assessment 01-Jan-18 10-Jan-18 The focus should be given on the clear understanding on investigation of speech to speech summarization with the use of machine learning program Completion of the undertaken research 11-Jan-18 20-Jan-18 Submission of the research undertaken on the topic Investigation on the machine learning and data mining activities associated with the speech to speech and speech to text summarization Budget The budget allocated for conducting the research study is around $ 6000 on investigation of speech to speech data mining techniques. $ 1200 is allocated for conducting the literature review and collecting data from research methodologies. $ 1200 is used for data collection and data analysis for finding the result of the undertaken research. $ 2500 is spent on traveling allowance. $ 1100 are used for conducting experiments for the analysis of the error occurred in the process of data mining in the speech to speech summarization. The following table shows the distribution of the budget allocated to the research study. Activities Allocated budget literature review and collecting data from research methodologies $ 1200 Data collection and data analysis for finding the result of the undertaken research $ 1200 Traveling allowance $ 1500 Conducting experiments for the analysis of the error occurred in the process of data mining in the speech to speech summarization $ 1100 Development of the research report $ 1000 Total estimated cost $ 6000 Research limitation The limitation of the research is the number of samples used for study. The sub-analysis of the finding has not been done (Nenkova, 2016). The proposed budget and time is inefficient in handling the research proposal. Constraints: The major constraints associated with the speech text summarization are the concatenation of the words and the construction of the sentence. Ethical Issues: The miscommunication is the major problem which can give birth to the misunderstanding. The interpretation of the speaker language is wrongly done by the receiving units which creates the scenario of the misunderstanding. The intention and the emotion of the listener are misinterpreted by the receiver. Conclusion The purpose of this paper is to reduced errors from the construction of the sentence. The important sentence depends on the synchronization of the result achieved. The removal of the unwanted words helps in reducing the length of the sentence and reducing errors. The two phased protocol developing the compression ratio according to the demand of the sentence formation to achieve accuracy and minimizing errors in the sentence. The reliability of the method can be achieved by managing the occurrence of spontaneous speech. The errors is the deviation of the outcome from the expected results. The errors are categorised into two categories which are under generation and over generation. The insertion and deletion process is used for handling the errors in the construction of the sentence. The correction is recognized automatically for extracting the speech segmentation. The clarification of the request helps in confirmation of the concept for designing the error resistance model for the a ctivities undertaken to establish error resistance working model for the summarization of the speech to speech and speech to text model. The attenuation is inserted in the sentences for reducing the rat of errors in the construction of the sentences through the medium of speech recognition system. The effectiveness and efficiency can be improved of the sentence construction for managing the compression ratio of larger sentence to reduce the rate of error. References: Antino, H. (2012). Emerging technologies of text mining: Techniques and applications. 1st ed. [ebook]. [Accessed 06 Oct. 2017]. Berry, M. (2014). Survey of text mining: clustering, classification, and retrieval. 1st ed. [ebook]. [Accessed 06 Oct. 2017]. Bijuraj, L. (2013). Clustering and its applications. 1st ed. [ebook]. [Accessed 06 Oct. 2017]. Bramer, M. (2013). Research and development in intelligent system. 1st ed. [ebook]. [Accessed 06 Oct. 2017]. Cercone, N. (2012).Advances in knowledge discovery and data mining . 1st ed. [ebook]. [Accessed 06 Oct. 2017]. Chakraborty, G. (2014). Analysis of unstructured data: Application of text analytics and sentiment mining. [Accessed 06 Oct. 2017]. Dinoy, I. (2016). Methodological challenges and analytic opportunities for modelling and interpreting big data. 1st ed. [ebook]. [Accessed 06 Oct. 2017]. Furui, S. (2013). Speech to speech and speech to text summarization. 1st ed. [ebook]. [Accessed 06 Oct. 2017]. Garla, S. (2010). Text mining and analysis. 1st ed. [ebook]. [Accessed 06 Oct. 2017]. Gonzalez, G. (2015).Recent advances and emerging applications in text and data mining for biomedical discovery. [Accessed 06 Oct. 2017]. Govindraj, S. (2016). Intensified sentiments analysis of customers product review using acoustic and textual features. 1st ed. [ebook]. [Accessed 06 Oct. 2017]. Kang, S. (2013). Dialogue strategies to overcome speech recognition errors inform filling dialogue. [Accessed 06 Oct. 2017]. Kawle, A. (2013). Text to speech web plugin with text summarisation. 1st ed. [ebook]. [Accessed 06 Oct. 2017]. Koulali, R. (2011). Topic detection and multi-word terms extraction for Arabic unvowelized documents. 1st ed. [ebook]. [Accessed 06 Oct. 2017]. Liu, Y. (2006). A study on the machine learning from imbalanced data for sentence boundary detection in speech. 1st ed. [ebook]. [Accessed 06 Oct. 2017]. Moreno, A. (2012). Text analytics: The convergence of big data and artificial intelligence. 1st ed. [ebook]. [Accessed 06 Oct. 2017]. Najafabadi, M. (2012). Deep learning application and challenges in big data. 1st ed. [ebook]. [Accessed 06 Oct. 2017]. Nenkova, A. (2016). A survey of text summarization techniqies. 1st ed. [ebook]. [Accessed 06 Oct. 2017]. Neto, J. (2015). Automatic text summarization using a machine learning approach. 1st ed. [ebook]. [Accessed 06 Oct. 2017]. Perner, P. (2010). Machine learning and data mining in pattern recognition. 1st ed. [ebook]. [Accessed 06 Oct. 2017]. Solka, J. (2013). Text data mining theory and methods. 1st ed. [ebook]. [Accessed 06 Oct. 2017]. Zhong, N. (2012). Effective pattern discovery for text mining. 1st ed. [ebook]. [Accessed 06 Oct. 2017].