The DOI matches its Crossref record; 14 of the 14 references it cites were found in a registry or an index.
Large scale discriminative training of hidden Markov models for speech recognition
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Citations
Cites
Leggetter, C. J., & Woodland, P. C. (1995) · Computer Speech & Language · doi:10.1006/csla.1995.0010 · Cited by 2,192
Self-citationMaximum likelihood linear transformations for HMM-based speech recognition
Gales, M. J. F. (1998) · Computer Speech & Language · doi:10.1006/csla.1998.0043 · Cited by 1,482
Tree-based state tying for high accuracy acoustic modelling
Young, S. J., Odell, J. J., & Woodland, P. C. (1994) · Proceedings of the workshop on Human Language Technology - HLT '94 · doi:10.3115/1075812.1075885 · Cited by 664
Self-citationMean and variance adaptation within the MLLR framework
Gales, M. J. F., & Woodland, P. C. (1996) · Computer Speech & Language · doi:10.1006/csla.1996.0013 · Cited by 393
Self-citationFinding consensus among words: lattice-based word error minimization
Mangu, L., Brill, E., & Stolcke, A. (1999) · 6th European Conference on Speech Communication and Technology · doi:10.21437/eurospeech.1999-127 · Cited by 214
An inequality for rational functions with applications to some statistical estimation problems
Gopalakrishnan, P. S., Kanevsky, D., Nadas, A., & Nahamoo, D. (1991) · IEEE Transactions on Information Theory · doi:10.1109/18.61108 · Cited by 197
MMIE training of large vocabulary recognition systems
Valtchev, V, Odell, J. J., Woodland, P. C., & Young, S. J. (1997) · Speech Communication · doi:10.1016/s0167-6393(97)00029-0 · Cited by 175
Self-citationNadas, A. J. (1983) · IEEE Transactions on Acoustics Speech and Signal Processing · doi:10.1109/tassp.1983.1164173 · Cited by 116
MMI training for continuous phoneme recognition on the TIMIT database
Kapadia, S., Valtchev, V., & Young, S. J. (1993) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp.1993.319349 · Cited by 94
Minimum error rate training based on N-best string models
Chou, W., Lee, C.-H., & Juang, B.-H. (1993) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp.1993.319394 · Cited by 81
On a model-robust training method for speech recognition
Nadas, A. J., Nahamoo, D., & Picheny, M. (1988) · IEEE Transactions on Acoustics Speech and Signal Processing · doi:10.1109/29.90371 · Cited by 79
Normandin, Y., & Morgera, S. D. (1991) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp.1991.150395 · Cited by 73
Frame discrimination training for HMMs for large vocabulary speech recognition
Povey, D., & Woodland, P. C. (1999) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp.1999.758130 · Cited by 37
Self-citationHidden Markov model/neural network training techniques for connected alphadigit speech recognition
Hochberg, M. M., Niles, L. T., Foote, J. T., & Silverman, H. F. (1991) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp.1991.150290 · Cited by 11
Cited by
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
Minimum Phone Error and I-smoothing for improved discriminative training
Povey, D., & Woodland, P. C. (2002) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp.2002.5743665 · Cited by 622
Self-citationSpoken Language Recognition: From Fundamentals to Practice
Li, H., Ma, B., & Lee, K. A. (2013) · Proceedings of the IEEE · doi:10.1109/jproc.2012.2237151 · Cited by 296
Metadata
- Authors
- Woodland, P. C., & Povey, D.
- Venue
- Computer Speech & Language
- Publisher
- Elsevier BV
- Published
- 2002-01
- Volume
- 16
- Issue
- 1
- Pages
- 25-47
- ISSN
- 0885-2308 (ISSN-L)
- OpenAlex
- W2003123121
- Cited by
- 306
- References
- 14
- FWCI
- 17.40
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
