The DOI matches its Crossref record; 32 of the 32 references it cites were found in a registry or an index.
An overview of the SPHINX speech recognition system
Abstract
A description is given of SPHINX, a system that demonstrates the feasibility of accurate, large-vocabulary, speaker-independent, continuous speech recognition. SPHINX is based on discrete hidden Markov models (HMMs) with LPC- (linear-predictive-coding) derived parameters. To provide speaker independence, knowledge was added to these HMMs in several ways: multiple codebooks of fixed-width parameters, and an enhanced recognizer with carefully designed models and word-duration modeling. To deal with coarticulation in continuous speech, yet still adequately represent a large vocabulary, two new subword speech units are introduced: function-word-dependent phone models and generalized triphone models. With grammars of perplexity 997, 60, and 20, SPHINX attained word accuracies of 71, 94, and 96%, respectively, on a 997-word task.>
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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 1,212
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Jelinek, F. (1976) · Proceedings of the IEEE · doi:10.1109/proc.1976.10159 · Cited by 920
Subdivision of the Audible Frequency Range into Critical Bands (Frequenzgruppen)
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Interpolated estimation of Markov source parameters from sparse data
Jelinek, F. (1980) · Medical Entomology and Zoology · Cited by 823
Speaker-independent isolated word recognition using dynamic features of speech spectrum
Furui, S. (1986) · IEEE Transactions on Acoustics, Speech, and Signal Processing · doi:10.1109/tassp.1986.1164788 · Cited by 748
Cited by
The SPHINX-II speech recognition system: an overview
Huang, X., Alleva, F., Hon, H.-W., Hwang, M.-Y., Lee, K.-F., & Rosenfeld, R. (1993) · Computer Speech & Language · doi:10.1006/csla.1993.1007 · Cited by 368
Self-citationSerendipity: enabling remote computing among intermittently connected mobile devices
Shi, C., Lakafosis, V., Ammar, M. H., & Zegura, E. W. (2012) · Proceedings of the thirteenth ACM international symposium on Mobile Ad Hoc Networking and Computing · doi:10.1145/2248371.2248394 · Cited by 340
Adaptive Statistical Language Modeling: A Maximum Entropy Approach
Rosenfeld, R. (2018) · doi:10.1184/r1/6603032 · Cited by 269
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Metadata
- Authors
- Lee, K.-F., Hon, H.-W., & Reddy, R.
- Venue
- IEEE Transactions on Acoustics, Speech, and Signal Processing
- Published
- 1990
- Volume
- 38
- Issue
- 1
- Pages
- 35-45
- ISSN
- 0096-3518 (ISSN-L)
- OpenAlex
- W2158791054
- Cited by
- 440
- References
- 32
- FWCI
- 20.18
- Type
- journal article
- Language
- en
- Open access
- closed
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