The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.
Hidden Markov Models for Speech Recognition
Abstract
The use of hidden Markov models for speech recognition has become predominant in the last several years, as evidenced by the number of published papers and talks at major speech conferences. The reasons this method has become so popular are the inherent statistical (mathematically precise) framework; the ease and availability of training algorithms for cstimating the parameters of the models from finite training sets of speech data; the flexibility of the resulting recognition system in which one can easily change the size, type, or architecture of the models to suit particular words, sounds, and so forth; and the ease of implementation of the overall recognition system. In this expository article, we address the role of statistical methods in this powerful technology as applied to speech recognition and discuss a range of theoretical and practical issues that are as yet unsolved in terms of their importance and their effect on performance for different system implementations.
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Maximum Likelihood from Incomplete Data Via the EM Algorithm
Dempster, A. P., Laird, N. M., & Rubin, D. B. (1977) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1977.tb01600.x · Cited by 50,444
A tutorial on hidden Markov models and selected applications in speech recognition
Rabiner, L. R. (1989) · Proceedings of the IEEE · doi:10.1109/5.18626 · Cited by 22,743
Self-citationAn Algorithm for Vector Quantizer Design
Linde, Y., Buzo, A., & Gray, R. (1980) · IEEE Transactions on Communications · doi:10.1109/tcom.1980.1094577 · Cited by 7,201
An introduction to hidden Markov models
Rabiner, L., & Juang, B. (1986) · IEEE ASSP Magazine · doi:10.1109/massp.1986.1165342 · Cited by 4,775
Self-citationMaximum mutual information estimation of hidden Markov model parameters for speech recognition
Bahl, L., Brown, P., de Souza, P., & Mercer, R. (2005) · ICASSP '86. IEEE International Conference on Acoustics, Speech, and Signal Processing · doi:10.1109/icassp.1986.1169179 · Cited by 817
Explicit modelling of state occupancy in hidden Markov models for automatic speech recognition
Russell, M., & Moore, R. (1985) · ICASSP '85. IEEE International Conference on Acoustics, Speech, and Signal Processing · doi:10.1109/icassp.1985.1168477 · Cited by 194
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Baltrusaitis, T., Ahuja, C., & Morency, L.-P. (2019) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2018.2798607 · Cited by 5,018
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Real-time American sign language recognition using desk and wearable computer based video
Starner, T., Weaver, J., & Pentland, A. (1998) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.735811 · Cited by 1,335
Recognizing human action in time-sequential images using hidden Markov model
Yamato, J., Ohya, J., & Ishii, K. (2003) · Proceedings 1992 IEEE Computer Society Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.1992.223161 · Cited by 1,273
Real-time American Sign Language recognition from video using hidden Markov models
Starner, T., & Pentland, A. (2002) · Proceedings of International Symposium on Computer Vision - ISCV · doi:10.1109/iscv.1995.477012 · Cited by 773
Metadata
- Authors
- Juang, B. H., & Rabiner, L. R.
- Venue
- Technometrics
- Publisher
- Informa UK Limited
- Published
- 1991-08
- Volume
- 33
- Issue
- 3
- Pages
- 251-272
- ISSN
- 0040-1706 (ISSN-L)
- 1537-2723
- OpenAlex
- W2003333103
- Cited by
- 1,068
- References
- 6
- FWCI
- 13.81
- Type
- journal article
- Language
- en
- Open access
- closed
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