Hindi Automatic Speech Recognition Using HTK
Journal Title: INTERNATIONAL JOURNAL OF ENGINEERING TRENDS AND TECHNOLOGY - Year 2013, Vol 4, Issue 6
Abstract
Automated Speech Recognition (ASR) is the ability of a machine or program to recognize the voice commands or take dictation which involves the ability to match a voice pattern against a provided or acquired vocabulary. At present, mainly Hidden Markov Model (HMMs) based speech recognizers are used. This paper aims to build a speech recognition system for Hindi language. Hidden Markov Model Toolkit (HTK) is used to develop the system. It recognizes the isolated words using acoustic word model. The system is trained for 113 Hindi words. Training data has been collected from ninespeakers. The experimental results show that the overall accuracy of the presented system with 10 states in HMM topology is 96.61 and 95.49%.
Authors and Affiliations
Preeti Saini1 , Parneet Kaur2 , Mohit Dua
Keywords
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