The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.
HMM adaptation using vector taylor series for noisy speech recognition
Abstract
In this paper we address the problem of robustness of speech recognition systems in noisy environments. The goal is to estimate the parameters of a HMM that is matched to a noisy environment, given a HMM trained with clean speech and knowledge of the acoustical environment. We propose a method based on truncated vector Taylor series that approximates the performance of a system trained with that corrupted speech. We also provide insight on the approximations used in the model of the environment and compare them with the lognormal approximation in PMC. 1.
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Citations
Cites
Davis, S., & Mermelstein, P. (1980) · IEEE Transactions on Acoustics, Speech, and Signal Processing · doi:10.1109/tassp.1980.1163420 · Cited by 5,465
Speech recognition in noisy environments
Moreno, P. J. (1996) · Cited by 289
Model-based techniques for noise robust speech recognition
Gales, M. (1995) · Cambridge University Engineering Department Publications Database · Cited by 275
Large-vocabulary speech recognition under adverse acoustic environments
Deng, L., Acero, A., Plumpe, M., & Huang, X. (2000) · 6th International Conference on Spoken Language Processing (ICSLP 2000) · doi:10.21437/icslp.2000-657 · Cited by 222
Self-citationAcoustical and Environmental Robustness in Automatic Speech Recognition
Acero, A. (1993) · Cited by 116
Self-citationMulti-microphone correlation-based processing for robust speech recognition
Sullivan, T. M., & Stern, R. M. (1993) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp.1993.319238 · Cited by 50
Cited by
Deep Learning: Methods and Applications
Deng, L. (2014) · now publishers, Inc. eBooks · doi:10.1561/9781601988157 · Cited by 1,759
Self-citationAn investigation of deep neural networks for noise robust speech recognition
Seltzer, M. L., Yu, D., & Wang, Y. (2013) · 2013 IEEE International Conference on Acoustics, Speech and Signal Processing · doi:10.1109/icassp.2013.6639100 · Cited by 640
Interacting with computers by voice: automatic speech recognition and synthesis
O'Shaughnessy, D. (2003) · Proceedings of the IEEE · doi:10.1109/jproc.2003.817117 · Cited by 132
Metadata
- Authors
- Acero, A., Deng, L., Kristjansson, T., & Zhang, J.
- Venue
- 6th International Conference on Spoken Language Processing (ICSLP 2000)
- Publisher
- ISCA
- Published
- 2000-10-16
- Pages
- vol. 3, 869-872-0
- OpenAlex
- W1573570773
- Cited by
- 278
- References
- 6
- FWCI
- 3.66
- Type
- conference paper
- Language
- en
- Open access
- closed
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- Acero, A., Deng, L., Kristjansson, T., & Zhang, J. (2000). HMM adaptation using vector taylor series for noisy speech recognition. 6th International Conference on Spoken Language Processing (ICSLP 2000). https://doi.org/10.21437/icslp.2000-672
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