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Trainable grammars for speech recognition
Open accessAbstract
Algorithms which are based on modeling speech as a finite-state, hidden Markov process have been very successful in recent years. This paper presents a generalization of these algorithms to certain denumerable-state, hidden Markov processes. This algorithm permits automatic training of the stochastic analog of an arbitrary context free grammar. In particular, in contrast to many grammatical inference methods, the new algorithm allows the grammar to have an arbitrary degree of ambiguity. Since natural language is often syntactically ambiguous, it is necessary for the grammatical inference algorithm to allow for this ambiguity. Furthermore, allowing ambiguity in the grammar allows errors in the recognition process to be explicitly modeled in the grammar rather than added as an extra component.
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Citations
Cited by
Zettlemoyer, L., & Collins, M. (2012) · arXiv (Cornell University) · doi:10.48550/arxiv.1207.1420 · Cited by 728
Applications of stochastic context-free grammars using the Inside-Outside algorithm
Lari, K., & Young, S. J. (1991) · Computer Speech & Language · doi:10.1016/0885-2308(91)90009-f · Cited by 639
Recurrent Neural Network Grammars
Dyer, C., Kuncoro, A., Ballesteros, M., & Smith, N. A. (2016) · Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies · doi:10.18653/v1/n16-1024 · Cited by 517
Inside-outside reestimation from partially bracketed corpora
Pereira, F., & Schabes, Y. (1992) · Proceedings of the 30th annual meeting on Association for Computational Linguistics - · doi:10.3115/981967.981984 · Cited by 284
Metadata
- Authors
- Baker, J. K.
- Venue
- The Journal of the Acoustical Society of America
- Publisher
- Acoustical Society of America (ASA)
- Published
- 1979-06-01
- Volume
- 65
- Issue
- S1
- Pages
- S132-S132
- ISSN
- 0001-4966 (ISSN-L)
- 1520-8524
- OpenAlex
- W2047706513
- Cited by
- 512
- References
- 0
- Type
- conference abstract
- Language
- en
- Open access
- bronze
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- Baker, J. K. (1979). Trainable grammars for speech recognition. The Journal of the Acoustical Society of America. https://doi.org/10.1121/1.2017061
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