Gender Effect Canonicalization for Bangla ASR
Journal Title: International Journal of Advanced Computer Science & Applications - Year 2012, Vol 3, Issue 11
Abstract
This paper presents a Bangla (widely used as Bengali) automatic speech recognition system (ASR) by suppressing gender effects. Gender characteristic plays an important role on the performance of ASR. If there is a suppression process that represses the decrease of differences in acoustic-likelihood among categories resulted from gender factors, a robust ASR system can be realized. In the proposed method, we have designed a new ASR incorporating the Local Features (LFs) instead of standard mel frequency cepstral coefficients (MFCCs) as an acoustic feature for Bangla by suppressing the gender effects, which embeds three HMM-based classifiers for corresponding male, female and geneder-independent (GI) characteristics. In the experiments on Bangla speech database prepared by us, the proposed system has achieved a significant improvement of word correct rates (WCRs), word accuracies (WAs) and sentence correct rates (SCRs) in comparison with the method that incorporates Standard MFCCs.
Authors and Affiliations
B. K. M Mizanur Rahman , Bulbul Ahamed , Md. Asfak-Ur-Rahman , Khaled Mahmud , Mohammad Nurul Huda
Keywords
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- EP ID EP114528
- DOI 10.14569/IJACSA.2012.031115
- Views 93
- Downloads 0
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