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JSIR Vol.69(07) [July 2010] >


Title: Performance analysis of voice activity detection algorithm for robust speech recognition system under different noisy environment
Authors: Babu, C Ganesh
Vanathi, P T
Ramachandran, R
Rajaa, M Senthil
Vengatesh, R
Keywords: Hidden Markov model (HMM)
Subband OSF based voice activity detection (VAD)
Vector quantization
Issue Date: Jul-2010
Publisher: CSIR
Abstract: This study evaluates performance of objective measures in terms of predicting quality of noisy input speech signal usingvoice activity detection (VAD). Implementation process includes a speech-to-text system using isolated word recognition with avocabulary of 10 words (digits 0-9) and statistical modeling (Hidden Markov Model - HMM) for machine speech recognition. Intraining period, uttered digits were recorded using 8-bit pulse code modulation (PCM) with a sampling rate of 8 KHz and save asa wave format file using sound recorder software. HMM performs speech analysis using linear predictive coding (LPC) methodof degree. For a given word in vocabulary, system builds an HMM model and trains model during training phase. Training stepsfrom VAD to HMM model building are performed using PC-based Matlab programs. Current framework uses automatic speechrecognition (ASR) with HMM based classification and noise language modeling to achieve effective noise knowledge estimation.
Page(s): 515-522
ISSN: 0975-1084 (Online); 0022-4456 (Print)
Source:JSIR Vol.69(07) [July 2010]

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