Jurassic Park Extrapolation Renders Speech to Speech Engine Greater Accuracy

Abstract Many people as they age face a greater challenge of muscular dexterity around their facial muscles. This results in difficulty producing certain sounds, and sometimes the problem is so severe that they are unintelligible. People who could benefit from the methods in this paper are those who are hard of hearing and do not have feedback readily accessible and<br>people with ALS. This paper describes a method that uses a computer learning algorithm that predicts what people are about to say based on previous content and learns what the natural sound of their voice are. A progressing conversation makes an increasingly accurate sentence trajectory. By using statistics of a conversation from its conception to a current point, Clear Audio validates the spoken voice and if a sound does not seemgood enough to understand, it shapes it into something that is more intelligible. The emphasis of this paper is to explain about the speech trajectory and voice shaping. I am currently developing software to help the users of Android and IOS smart phones to communicate more efficiently using the concepts discussed in this paper.<br>Keywords Speech Recognition, Natural Language Processing, Artificial Neural Network, Verbal Apraxia