A Voice Signal Interpreter using Machine Learning Techniques
Keywords:
Neural network, machine translator, Text to speech Translator, perceptron modelAbstract
As we all know computer generated speech in immense now a days. In the current era of IT usage of computer generated speech is in great demand where as these speeches are still not human, and it`s not easy on the ears. The production quality system like Google Assistant, Apple Siri, Amazon Alexa, or Bixby as different from what a human generated speech would sound like. Many advances have been made in speech synthesis using neural network for easy accessing. Prime goal of this paper is to create an interpreter (Machine translator), to translate text to speech using a neural network. In this paper the main objective is to combine two techniques to produce a new product i.e. a new version of the translator. An artificial communicator is being developed to communicate with the universal language that is English for communication in between System & humans. These two technologies are used to link with each other & competence thoroughly. The purpose of this Application software is to permit different picture to convert its text in a language which is displayed in vocalizations. And it also permits for weakening vision in worst case seen in fields in picture format to understand language. A skill is being generated in machine through software for the Suitableness of humans for easy accessing.
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