Speech to text Conversion using Deep Learning Neural Net Methods (Turkish Journal of Computer and Mathematics Education (TURCOMAT), 2022)
Internet has grown in the past and has transformed several fields and changed numerouslives. Internet can be a blessing for humanity. The primary field that has been transformed byinternet technology is communication. Internet has allowed speedier and simplercommunication. In this paper, we intend to explore the various methods for conversion ofspeech-to-text that can be utilized in an email system that is based on voice. This method isbuilt on the interactive voice response. The goal is to research and evaluate the differentmethods that are used in STT conversions, and find the most efficient method that is able tobe adapted to both conversion processes. In the end, based on a review study, it has beendiscovered that HMM using deep neural networks is the most effective statistical model , andtherefore the best for STT. In the end, a model that uses HMM and ANN techniques toconvert STT conversion is suggested.