The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Maximum mutual information estimation of hidden Markov model parameters for speech recognition
Abstract
A method for estimating the parameters of hidden Markov models of speech is described. Parameter values are chosen to maximize the mutual information between an acoustic observation sequence and the corresponding word sequence. Recognition results are presented comparing this method with maximum likelihood estimation.
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Cites
Baum, L. E. (1972) · Medical Entomology and Zoology · Cited by 1,405
A Maximum Likelihood Approach to Continuous Speech Recognition
Bahl, L. R., Jelinek, F., & Mercer, R. L. (1983) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.1983.4767370 · Cited by 1,220
Self-citationSome experiments with large-vocabulary isolated-word sentence recognition
Bahl, L. R., Das, S. K., de Souza, P., Jelinek, F., Katz, S., Mercer, R. L., & Picheny, M. (2005) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp.1984.1172520 · Cited by 19
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Gradient-based learning applied to document recognition
Lecun, Y., Bottou, L., Bengio, Y., & Haffner, P. (1998) · Proceedings of the IEEE · doi:10.1109/5.726791 · Cited by 58,805
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
Hinton, G., Deng, L., Yu, D., Dahl, G., Mohamed, A.-R., Jaitly, N., Senior, A., Vanhoucke, V., Nguyen, P., Sainath, T., et al. (2012) · IEEE Signal Processing Magazine · doi:10.1109/msp.2012.2205597 · Cited by 10,260
Why Does Unsupervised Pre-training Help Deep Learning?
Erhan, D., Bengio, Y., Courville, A. C., Manzagol, P.-A., Vincent, P., & Samy Bengio, A. (2010) · Cited by 2,180
A Diversity-Promoting Objective Function for Neural Conversation Models
Li, J., Galley, M., Brockett, C., Gao, J., & Dolan, B. (2016) · Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT) · doi:10.18653/v1/n16-1014 · Cited by 2,459
Metadata
- Authors
- Bahl, L., Brown, P., de Souza, P., & Mercer, R.
- Affiliations
- IBM Research - Thomas J. Watson Research Center (US)
- Venue
- ICASSP '86. IEEE International Conference on Acoustics, Speech, and Signal Processing
- Published
- 2005-03-24
- Volume
- 11
- Pages
- 49-52
- ISSN
- 1520-6149 (ISSN-L)
- OpenAlex
- W1877570817
- Cited by
- 817
- References
- 3
- Citations by year
- 2026: 1 · 2025: 9 · 2024: 13 · 2023: 11 · 2022: 16 · 2021: 30 · 2020: 25 · 2019: 30 · 2018: 33 · 2017: 24 · 2016: 25 · 2015: 34 · 2014: 42 · 2013: 29 · 2012: 39
- FWCI
- 28.55
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- IEEE International Conference on Acoustics Speech and Signal Processing (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Speech Recognition and Synthesis
- Physical Sciences › Computer Science › Signal Processing › Speech and Audio Processing
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Phonetics and Phonology Research
- Keywords
- hidden Markov models, parameter estimation, mutual information maximization, speech recognition, word sequences, maximum likelihood estimation comparison
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