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An overview of the SPHINX speech recognition system
K. Lee, H. Hon, and R. Reddy
IEEE Transactions on Acoustics, Speech and Signal Processing, Vol. 38, No. 1, January, 1990, pp. 35 - 45.

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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.

Note: see also IEEE Transactions on Signal Processing

K. Lee, H. Hon, and R. Reddy, "An overview of the SPHINX speech recognition system," IEEE Transactions on Acoustics, Speech and Signal Processing, Vol. 38, No. 1, January, 1990, pp. 35 - 45.

@article{Lee_1990_3707,
   author = "K.-F. Lee and H.-W. Hon and Raj Reddy",
   title = "An overview of the SPHINX speech recognition system",
   journal = "IEEE Transactions on Acoustics, Speech and Signal Processing",
   month = "January",
   year = "1990",
   volume = "38",
   number = "1",
   pages = "35 - 45",
   note = "see also IEEE Transactions on Signal Processing"
}