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- W2079713242 abstract "Abstract This paper describes recent and future work on the sphinx speech recognition system at Carnegie Mellon. Sphinx is a large-vocabulary speaker-independent continuous speech recognizer based on discrete hidden Markov models. Sphinx uses multiple codebooks of LPC-derived features, and phonetic units that model function words and phrases, as well as within and between word generalized triphones. Sphinx is first trained with the Forward-Backward algorithm, and then with the corrective training algorithm. On a 997-word task, sphinx attained accuracies of 96% with a grammar (perplexity 60), and 82% without grammar (perplexity 997). This paper describes the sphinx System and its performance in detail, as well as outlines our future work." @default.
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- W2079713242 date "1990-01-01" @default.
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- W2079713242 title "Recent progress and future outlook of the SPHINX speech recognition system" @default.
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- W2079713242 doi "https://doi.org/10.1016/0885-2308(90)90023-y" @default.
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