Speech to text Conversion using Deep Learning Neural Net Methods
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Abstract
Internet has grown in the past and has transformed several fields and changed numerous
lives. Internet can be a blessing for humanity. The primary field that has been transformed by
internet technology is communication. Internet has allowed speedier and simpler
communication. In this paper, we intend to explore the various methods for conversion of
speech-to-text that can be utilized in an email system that is based on voice. This method is
built on the interactive voice response. The goal is to research and evaluate the different
methods that are used in STT conversions, and find the most efficient method that is able to
be adapted to both conversion processes. In the end, based on a review study, it has been
discovered that HMM using deep neural networks is the most effective statistical model , and
therefore the best for STT. In the end, a model that uses HMM and ANN techniques to
convert STT conversion is suggested.
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