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Tamil Speech Recognizer Using Hidden Markov Model for Question Answering System of Railways

Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 325)

Abstract

The research on speech and natural language is in progress for more than two decades. Recently, researchers are focused on developing speech interfaces to their corresponding automated system. For voice-based question answering system, there is the need for developing speech recognizer. Although automatic speech recognition (ASR) systems are already available, most of them have been built for English language. This paper aims to build Tamil speech recognizer for question answering system of railway information using natural language processing. Most feasible approach for speech recognition so far has been hidden Markov model (HMM) which is implemented in this research work. HMM-based recognition component is trained automatically and computationally realistic to use. The recognition accuracy of the system using HMM has up to 85 % for different speakers.

Keywords

Automatic speech recognition Hidden Markov model Voice recording Word boundary detections Session initiation protocol 

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Copyright information

© Springer India 2015

Authors and Affiliations

  1. 1.Department of Information TechnologyNational Engineering CollegeKovilpattiIndia

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