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JSIR Vol.69 [2010] >
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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