Modelling and analysis of artificial intelligence approaches in enhancing the speech recognition for effective multi-functional machine learning platform – A multi regression modelling approach

Abstract

Speech is considered as the fundamental aspect of communication between human being, speech recognition is stated as the overall process to convert the sound into corresponding text based on a specific language. The implementation of speech recognition has supported individuals, business and others in order to possess better communication and interaction so as to realise its objectives. This been regarded as the process of collating text message or in some form of meaning based on the input received from voice of another individual. The speech analytics is stated as the key part in the speech recognition as it converts the individual voice into digital form so as to store them and transmit it as and when required using computing equipments.The speech synthesis is considered as the reversal of speech recognition as they convert the data from the digitised format into voice which supports the users to listen quickly and easily.The application of speech recognition in organisation is confined in building more interactive virtual assistants, supports the customers in addressing their queries and offer solutions at quick span of time, furthermore organisations can use speech recognition to identify the individuals so that they can access classified information or reset their password etc. The enhanced development in the technology domain has deepened the importance of artificial intelligence in different areas of work and life, The implementation of AI in speech recognition supports the business and individuals in apprehending better services to the stakeholders and perform the task in an efficient manner. Hence, this study is focused in analysing the key determinates of using AI in speech recognition for effective multifunctional Machine learning platform using regression analysis.