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題名：Improved Minimum Phone Error Based Discriminative Training of Acoustic Models for Mandarin Large Vocabulary Continuous Speech Recognition
書刊名：International Journal of Computational Linguistics & Chinese Language Processing
作者：Liu, Shih-hung／Chu, Fang-hui／Lo, Yueng-tien／Chen, Berlin
出版日期：2008
卷期：13:3
頁次：頁343-361
主題關鍵詞：Discriminative training；Minimum phone error；Phone accuracy function；Training data selection；Large vocabulary continuous speech recognition
原始連結：連回原系統網址new window
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  • 被引用次數被引用次數:期刊(0) 博士論文(0) 專書(0) 專書論文(0)
  • 排除自我引用排除自我引用:0
  • 共同引用共同引用:8
  • 點閱點閱:24
This paper considers minimum phone error (MPE) based discriminative training of acoustic models for Mandarin broadcast news recognition. We present a new phone accuracy function based on the frame-level accuracy of hypothesized phone arcs instead of using the raw phone accuracy function of MPE training. Moreover, a novel data selection approach based on the frame-level normalized entropy of Gaussian posterior probabilities obtained from the word lattice of the training utterance is explored. It has the merit of making the training algorithm focus much more on the training statistics of those frame samples that center nearly around the decision boundary for better discrimination. The underlying characteristics of the presented approaches are extensively investigated, and their performance is verified by comparison with the standard MPE training approach as well as the other related work. Experiments conducted on broadcast news collected in Taiwan demonstrate that the integration of the frame-level phone accuracy calculation and data selection yields slight but consistent improvements over the baseline system.
期刊論文
1.Rabiner, Lawrence R.(1989)。A Tutorial on Hidden Markov Models and Selected Applications in Speech Recognition。Proceedings of the IEEE，77(2)，257-286。  new window
2.Wang, Hsin-min、Chen, Berlin、Kuo, Jen-wei、Cheng, Shih-sian(20050600)。MATBN: A Mandarin Chinese Broadcast News Corpus。International Journal of Computational Linguistics & Chinese Language Processing，10(2)，219-235。new window  new window
3.Aubert, X. L.(2002)。An Overview of Decoding Techniques for Large Vocabulary Continuous Speech Recognition。Computer Speech and Language，16，89-114。  new window
4.Ortmanns, S.、Ney, H.、Aubert, X. L.(1997)。A Word Graph Algorithm for Large Vocabulary Continuous Speech Recognition。Computer Speech and Language，11，43-72。  new window
5.Saon, G.、Padmanabhan, M.(2001)。Data-Driven Approach to Designing Compound Words for Continuous Speech Recognition。IEEE transactions on speech and audio processing，9(4)，327-332。  new window
6.Chen, B.、Kuo, J. W.、Tsai, W. H.(2005)。Lightly Supervised and Data-Driven Approaches to Mandarin Broadcast News Transcription。中文計算語言學期刊，10(1)，1-18。  new window
7.Gopalakrishnan, P.S.、Kanevsky, D.、Nahamoo, D.、Nádas, A.(1989)。A Generalization of the Baum Algorithm to Rational Obejective Funtions。Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing，631-634。  new window
8.Jiang, H.、Li, X.、Liu, C.(2006)。Large Margin Hidden Markov Models for Speech Recognition。IEEE Transactions on Audio, Speech, and Language Processing，14(5)，1584-1595。  new window
9.Kuo, J. W.、Liu, S. H.、Wang, H. M.、Chen, B.(2006)。An Empirical Study of Word Error Minimization Approaches for Mandarin Large Vocabulary Speech Recognition。中文計算語言學期刊，11(3)，201-222。  new window
會議論文
1.Gillick, L.、Cox, S. J.(1989)。Some statistical issues in the comparison of speech recognition algorithms。Glasgow。532-535。  new window
2.Du, J.、Liu, P.、Soong, F. K.、Zhou, J. L.、Wang, R. H.(2006)。Minimum Divergence Based Discriminative Training。Pittsburgh。2410-2413。  new window
3.Goldberger, J.(2003)。An Efficient Image Similarity Measure Based on Approximations of KL-Divergence between Two Gaussian Mixtures。France。370-377。  new window
4.Gibson, Matthew、Hain, T.(2006)。Hypothesis Spaces for Minimum Bayes Risk Traininig in Large Vocabulary Speech Recognition。Pittsburgh。2406-2409。  new window
5.Heigold, G.、Macherey, W.、Schluter, R.、Ney, H.(2005)。Minimum Exact Word Error Training。Cancun。186-190。  new window
6.Li, J.、Lee, C. H.、Yuan, M.(2006)。Soft Margin Estimation of Hidden Markov Model Parameters。Pittsburgh。2422-2425。  new window
7.Liu, S. H.、Chu, F. H.、Chen, B.(2007)。Improved MPE Based Discriminative Training of Acoustic Models for Mandarin Large Vocabulary Continous Speech Recognition。  new window
8.Liu, S. H.、Chu, F. H.、Lin, S.-H.、Chen, B.(2007)。Investigating Data Selection for Minimum Phone Error Training of Acoustic Models。Beijing。348-351。  new window
9.Misra, H.、Bourlard, H.(2005)。Spectral Entropy Feature in Full-Combination Multi-Stream for Robust ASR。Lisbon。2633-2636。  new window
10.Zheng, J.、Stolcke, A.。Improved Discriminative Training using Phone Lattices。Lisbon。  new window
學位論文
1.Kumar, Nanda(1997)。Investigation of Silicon-Auditory Models and Generalization of Linear Discriminant Analysis for Improved Speech Recognition，Maryland。  new window
2.Povey, D.(2007)。Discriminative Training for Large Vocabulary Speech Recognition，Peterhouse。  new window
圖書
1.Bahl, L. R.、Brown, Polly、De Souza, P. V.、Mercer, R. L.(1986)。Maximum Mutual Information Estimation of Hidden Markov Model Parameters for Speech Recognition。Proc. IEEE ICASSP - 86。Tokyo。  new window
2.Stolcke, A.(2000)。SRI language Modeling Toolkit, version 1.3.3。SRI language Modeling Toolkit, version 1.3.3。  new window
3.Povey, D.、Kingsbury, B.(2007)。Evaluation of Proposed Modifications to MPE for Large Scales Discriminative Training。Proc. IEEE Int. Conf. Acoustics, Speech, Signal Processing。Hawaii。  new window
4.Povey, D.、Woodland, P. C.(2002)。Minimum Phone Error and I-smoothing for Improved Discriminative Training。Proc. IEEE Int. Conf. Acoustics, Speech, Signal Processing。Florida。  new window
5.Saon, G.、Padmanabhan, M.、Gopinath, R.、Chen, Sylvia(2000)。Maximum likelihood discriminant feature spaces。Proc. IEEE Int. Conf. Acoustics, Speech, Signal Processing。Istanbul。  new window
6.Wessel, F.、Schluter, R.、Ney, H.(2001)。Explicit Word Error Minimization Using Word Hypothesis Posterior Probabilities。Proc. IEEE Int. Conf. Acoustics, Speech, Signal Processing。Salt Lake City。  new window
其他
1.Wessel, F.，Schluter, R.，Ney, H.(2001)。Explicit Word Error Minimization Using Word Hypothesis Posterior Probabilities，Salt-Lake City, USA。  new window
 
 
 
 
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