Abstract
This chapter describes the application of Generalized LR parsing to speech recognition. In particular, we will focus on a method called HMM-LR, first introduced by [5], which is an integration of Hidden Markov Models and Generalized LR parsing.
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References
Baum, L. E., Petrie, T., Soules, G., & Weiss, N., 1970, A Maximization Technique Occurring in the Statistical Analysis of Probabilistic Functions of Markov Chains, The Annals of Mathematical Statistics, Vol. 41.
Fu, K.S., 1974, Syntactic Methods in Pattern Recognition, Academic Press.
Hanazawa, T., Kita, K., Nakamura, S., Kawabata, T., & Shikano, K., 1990, ATR HMM-LR Continuous Speech Recognition System, Proc. of ICASSP 90-IEEE International Conference on Acoustics, Speech and Signal Processing.
Kawabata, T., Shikano, K., & Kita, K., 1989, Task entropy and Phone Perplexity, The Acoustic Society of Japan Spring Meeting Proc. (in Japanese).
Kita, K., Kawabata, T., & Saito, H., 1989, HMM Continuous Speech Recognition Using Predictive LR Parsing, Proc. of ICASSP 89-IEEE International Conference on Acoustics, Speech and Signal Processing.
Kita, K., Kawabata, T., & Hanazawa, T., 1990, HMM Continuous Speech Recognition Using Stochastic Language Models, Proc. of ICASSP 90-IEEE International Conference on Acoustics, Speech and Signal Processing.
Kuwabara, H., Takeda, K., Sagisaka, Y., Katagiri, S., Morikawa, S., & Watanabe, T., 1989, Construction of a Large-Scale Japanese Speech Database and its Management System, Proc. of ICASSP 89-IEEE International Conference on Acoustics, Speech and Signal Processing.
Lee, K. F., Hon, H. W., & Reddy, R., 1990, An Overview of the SPHINX Speech Recognition System, IEEE Transactions on Acoustics, Speech, and Signal Processing, Vol. 38, No. 1.
Levinson, S. E., Rabiner, L.R., & Sondhi, M. M., 1983, An Introduction to the Application of the Theory of Probabilistic Functions of a Markov Process to Automatic Speech Recognition, Bell Syst. Tech. J., Vol. 62, No. 4.
Linde, Y., Buzo, A., & Gray, R. M., 1980, An Algorithm for Vector Quantizer Design, IEEE Transaction on Communications, COM-28.
Lippmann, R.P., 1989, Review of Neural Networks for Speech Recognition, Neural Computation, Vol. 1, No. 1.
Lowerre, B. & Reddy, R., 1980, The HARPY Speech Recognition System, in Trends in Speech Recognition, ed. Lea, W. A., Prentice-Hall.
Minami, Y, Sawai, H., Miyatake, M., & Shikano, K., 1990, Large Vocabulary Spoken Word Recognition Using Time-Delay Neural Network Phoneme Spotting and Predictive LR-Parsing, Trans. Tech. Group Speech Acoust. Soc. Japan, SP89-99 (in Japanese).
Morimoto, T., Ogura, K., Kita, K., Kogure, K., & Kakigahara, K., 1989, Spoken Language Processing in SL-TRANS, ATR Symposium on Basic Research for Telephone Interpretation.
Poritz, A.B., 1988, Hidden Markov Models: A Guided Tour, Proc. of ICASSP 88-IEEE International Conference on Acoustics, Speech and Signal Processing.
Rabiner, L. R., Juang, B.H., 1986, An Introduction to Hidden Markov Models, IEEE ASSP Magazine.
Shikano, K., 1987, Improvement of Word Recognition Results by Trigram Model, Proc. of ICASSP 87-IEEE International Conference on Acoustics, Speech and Signal Processing.
Waibel, A., Hanazawa, T., Hinton, G., Shikano, K., & Lang, K. J., 1989, Phoneme Recognition Using Time-Delay Neural Networks, IEEE Transactions on Acoustics, Speech, and Signal Processing, Vol. 37, No. 3.
Wright, J. H. & Wrigley, E. N., 1988, Linguistic Control in Speech Recognition, Proc. 7th FASE Symposium.
Zue, V., Glass, J., Phillips, M., & Seneff, S., 1989, Acoustic Segmentation and Phonetic Classification in the SUMMIT System, Proc. of ICASSP 89-IEEE International Conference on Acoustics, Speech and Signal Processing.
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Kita, K., Kawabata, T., Saito, H. (1991). GLR Parsing in Hidden Markov Model. In: Tomita, M. (eds) Generalized LR Parsing. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-4034-2_11
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DOI: https://doi.org/10.1007/978-1-4615-4034-2_11
Publisher Name: Springer, Boston, MA
Print ISBN: 978-1-4613-6804-5
Online ISBN: 978-1-4615-4034-2
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