Design and Development of an Acoustic-Based Recongnition System Using DNN

Abstract

Automatic speech recognition is a process of using computers to convert voice signals produced by human speech into reasonable format i.e. text or command that conveys the same meaning as the speaker intended to do. Many researchers are working on various languages including English and other European languages like Spanish, German, and French etc. to develop an automated system for speech recognition (ASR). However, researchers on the development of ASR for the Urdu language have put very little effort. We have developed an Urdu speech recognition system using Deep Neural Network (DNN) on our developed corpus that contains some of the most frequently used words in Urdu like digits, season names, and month names. The accuracy rates of our ASR are very encouraging because 72% accuracy is achieved for 26 words and 92% accuracy is achieved separately for names of seasons.