@article{lee1990an,
author = {Lee, Kai-Fu and Hon, Hsiao-Wuen and Reddy, R.},
title = {An overview of the SPHINX speech recognition system},
year = {1990},
month = {April},
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.},
url = {http://approjects.co.za/?big=en-us/research/publication/an-overview-of-the-sphinx-speech-recognition-system/},
pages = {35-45},
journal = {IEEE Trans. Acoust. Speech Signal Process.},
volume = {38},
number = {1},
}