Abstract
SM has shown a better performance than HMM in connected word recognition system; however, no reports we have read show that SM has been applied in LVCSR as decoding acoustic model because of the restriction of its complexity. We have preliminarily built a SM based mandarin LVCSR system which adopts CART and global tying to tie the parameters in the triphone models and the fast SM algorithm, CF algorithm and two-level pruning to enhance the speed of decoding. The system achieves 87.09% syllable accuracy in Test-863 data corpus within 4 real times. We believe SM offers an alternative choice for LVCSR system though further research for its fast algorithms by rational utilization of its structure information.
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References
Ostendorf, M., Digalakis, V., Kimball, O.: From HMM’s to Segment Models: A Unified View of Stochastic Modeling for Speech Recognition. IEEE Trans. on Speech and Audio Processing 4(5), 360–378 (1996)
Huang, X.D., Acero, A., Hon, H.W.: Spoken Language Processing: A Guide to Theory, Algorithm and System Development. Prentice Hall PTR, Englewood Cliffs (2001)
Ostendorf, M., Roukos, S.: A Stochastic Segment Model for Phoneme Based Continuous Speech Recognition. IEEE Trans. on Acoustic, Speech and Signal Processing. 37(12), 1857–1869 (1989)
Tang, Y., Liu, W.J., Zhang, Y.Y., Xu, B.: A Framework for Fast Segment Model by Avoidance of Redundant Computation on Segment. In: ISCSLP, Hong Kong, pp. 117–120 (2004)
Digalakis, V., Ostendorf, M., Rohlicek, J.: Fast Algorithms for Phone Classification and Recognition Using Segment-based Models. IEEE Trans. on Signal Processing 40(12), 2885–2896 (1992)
Gao, S., et al.: Acoustic Modeling for Chinese Speech Recognition: A Comparative Study of Mandarin and Cantonese. In: ICASSP, Istanbul, pp. 967–970 (2000)
Ney, H., Ortmanns, S.: Progress in Dynamic Programming Search for LVCSR. Proceedings of the IEEE 88(8), 1224–1240 (2000)
Young, S., et al.: The HTK Book, Cambridge (2002)
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© 2009 Springer-Verlag Berlin Heidelberg
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Liu, W., Tang, Y., Peng, S. (2009). Research on Segment Acoustic Model Based Mandarin LVCSR. In: Yu, W., He, H., Zhang, N. (eds) Advances in Neural Networks – ISNN 2009. ISNN 2009. Lecture Notes in Computer Science, vol 5552. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01510-6_105
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DOI: https://doi.org/10.1007/978-3-642-01510-6_105
Publisher Name: Springer, Berlin, Heidelberg
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