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- W1634541166 abstract "The paper describes the development of three alternative techniques for the classification of syllable stress in fluent speech. They are based on: (1) neural networks that use contextual syllabic information; (2) first and second order Markov chains that depend on a new dynamic vector quantization approach; and (3) a rule based approach. Both the neural network and the statistical approach achieved performance above 80%, with the neural networks slightly outperforming the Markov models. Experimental results also show that stress classification could enhance speech recognition." @default.
- W1634541166 created "2016-06-24" @default.
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- W1634541166 date "2002-12-24" @default.
- W1634541166 modified "2023-09-27" @default.
- W1634541166 title "Development and comparison of three syllable stress classifiers" @default.
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- W1634541166 doi "https://doi.org/10.1109/icslp.1996.607466" @default.
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