Title :
Duration modeling with expanded HMM applied to speech recognition
Author :
Bonafonte, Antonio ; Vidal, Josep ; Nogueiras, Albino
Author_Institution :
Univ. Politecnica de Catalunya, Barcelona, Spain
Abstract :
The occupancy of the HMM states is modeled by means of a Markov chain. A linear estimator is introduced to compute the probabilities of the Markov chain. The distribution function (DF) represents accurately the observed data. Representing the DF as a Markov chain allows the use of standard HMM recognizers. The increase of complexity is negligible in training and strongly limited during recognition. Experiments performed on acoustic-phonetic decoding shows how the phone recognition rate increases from 60.6 to 61.1. Furthermore, on a task of database inquires, where phones are used as subword units, the correct word rate increases from 88.2 to 88.4
Keywords :
decoding; hidden Markov models; probability; speech recognition; HMM state occupancy; Markov chain; acoustic-phonetic decoding; complexity; correct word rate; database inquires; distribution functions; duration modeling; expanded HMM; linear estimator; phone recognition rate; probabilities; speech recognition; standard HMM recognizers; subword units; training; Computational complexity; Databases; Decoding; Distribution functions; Hidden Markov models; Parameter estimation; Probability density function; Speech recognition; State estimation; Training data;
Conference_Titel :
Spoken Language, 1996. ICSLP 96. Proceedings., Fourth International Conference on
Conference_Location :
Philadelphia, PA
Print_ISBN :
0-7803-3555-4
DOI :
10.1109/ICSLP.1996.607797
