STUDIES OF AN ADVANCED AUDITORY MODEL AND THE APPLICATION TO IMPROVE THE ROBUSTNESS OF CONTINUOUS SPEECH RECOGNITION
STUDIES OF AN ADVANCED AUDITORY MODEL AND THE APPLICATION TO IMPROVE THE ROBUSTNESS OF CONTINUOUS SPEECH RECOGNITION
批准号:
10650358
负责人:
TANIGUCHI Shuji
金额:
$2.24万
依托单位:
依托单位国家:
日本
项目类别:
Grant-in-Aid for Scientific Research (C)
财政年份:
1998
资助国家:
日本
项目状态:
已结题
起止时间:
1998 至 2000
中文摘要
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英文摘要
Our final goal is to develop a reliable continuous speech recognition system based on a model of human auditory system. So, we have studied as follows :(1) On the base of a subword-unit-based isolated word recognizer (VQ-SWR) with the discrete hidden Markov models (DHMMs) as a recognition tool, which we developed before, the research to improve the robustness for speakers and some environment noises have been done. As experimental results, findings can be summarized as follows :[1] A new recognizer with the DHMMs replaced with the semi-continuous HMMs have been developed. Experimental results showed a considerable improvement of the new recognizer in speakerindependency.[2] We have developed a new subword-unit-based isolated word recognizer incorporated a multiparty and a speaker adaptation step on the base of the VQ-SWR.This is made up of DHMMs and a learning vector quantizer (LVQ) incorporated a feedback of information on the classification of input subword which is obtained from the … More output of the LVQ.Experimental results showed that the new recognizer performance including the robustness for speaker and noise in stationary states is higher than those accomplished with the conventional recognizer VQ-SWR.(2) To aim at achieving higher word recognition rates and higher noise robustness than the VQ-SWR, we have proposed a new recognizer (CM-RN-SWR) made up of a model (NLF-COM) of human cochlea called "a nonlinear feedback model for cochlea", a simple multi-layer recurrent neural network (RNN) which has feedback connections of self-loop type, and DHMMs for words. The NLF-COM and the RNN which were developed before by us has been used as a model of the human auditory system, and as a kind of spectrum analyzer for speech sounds and a subword recognizer, respectively. Experimental results showed that recognition accuracies for clean speech and speech in the presence of pseud-white noise are considerably improved in speaker-dependent applications in comparison with the VQ-SWR. Less
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橋詰和永: "単語認識システムにおけるロバストなセグメンテーション法(II)"平成11年度電気関係学会北陸支部連合大会講演論文集. 142 (1999)
Kazunaga Hashizume:“单词识别系统的鲁棒分割方法(II)”1999 年电气工程学会北陆分会会议记录 142(1999)。
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H.Matsui, T.Koizumi, S.Suzuki, M.Mori, S.Taniguchi: "Improving the Noise Robustness of Subword-Unit-Based Isolated Word Recognition System"Proceedings of the 2001 IEICE General Conference, Information and System 1. D-14-19. 189 (2001)
H.Matsui、T.Koizumi、S.Suzuki、M.Mori、S.Taniguchi:“提高基于子字单元的孤立词识别系统的噪声鲁棒性”2001 年 IEICE 大会记录,信息与系统 1.D
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小泉卓也: "サブワード単位離散単語認識システムの話者依存性の改善" 電子情報通信学会技術研究報告. SP98-47. 15-21 (1998)
Takuya Koizumi:“子词单元离散词识别系统的说话人依赖性的改进”IEICE SP98-47(1998)。
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向當一洋: "サブワード単位離散単語認識システムの話者依存性の改善"電子情報通信学会技術研究報告. SP98-47. 15-21 (1998)
Kazuhiro Mukai:“子词单元离散词识别系统的说话人依赖性的改进”IEICE SP98-47(1998)。
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Takuya Koizumi, Shuji Taniguchi, and Kazuhiro Kohtoh: "Improving the Speaker-Dependency of Subword-Unit-Based Isolated Word Recognition"Proceedings of 1998 International Conference on Spoken Language Processing (ICSLP 98). 2. 345-348 (1998)
Takuya Koizumi、Shuji Taniguchi 和 Kazuhiro Kohtoh:“改善基于子词单元的孤立词识别的说话人依赖性”1998 年国际口语处理会议 (ICSLP 98) 会议记录。
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