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  • 标题:Gender Effect Canonicalization for Bangla ASR
  • 本地全文:下载
  • 作者:B.K.M Mizanur Rahman ; Bulbul Ahamed ; Md. Asfak-Ur-Rahman
  • 期刊名称:International Journal of Advanced Computer Science and Applications(IJACSA)
  • 印刷版ISSN:2158-107X
  • 电子版ISSN:2156-5570
  • 出版年度:2012
  • 卷号:3
  • 期号:11
  • DOI:10.14569/IJACSA.2012.031115
  • 出版社:Science and Information Society (SAI)
  • 摘要: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.
  • 关键词:thesai; IJACSA; thesai.org; journal; IJACSA papers; Acoustic Model; AutomaticSpeech Recognition; Gender Effects Suppression; Hidden Markov Model.
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