共 10 条
[1]
From HMM’s to segment models: a unified view of stochastic modeling for speech recognition. Ostendorf M,Digalakis V,Kimball OA. IEEE Transactions on Speech and Audio Proceessing . 1996
[2]
Speech recognition using hidden Markov models with polynomial regression functions as non-stationary states. Deng L,Aksmanovic M,Sun D,et al. IEEE Transactions on Speech and Audio Processing . 1993
[3]
Vector quantization of pitch information in Mandarin speech. Chen S H,Wang Y R. IEEE Transactions on Communications . 1990
[4]
Explicit correlation in hidden Markovmodels for speech recognition.In Proceedings of ICASSP,San Francisco, CA,U. Wellekens P C. S.A . 1987
[5]
Use of temporal correlation between successive frames in hidden Markov model based speechrecognizer.In Proceedings of ICASSP, Minneapolis,MN,U. Paliwal K K. S.A . 1993
[6]
A linear predictiveMM for vector-valued observations with applications tospeech recognition. Kenny P,Lenning M,Mermelstein P. IEEE Trans. Acoust. SPeech SignalProcess . 1990
[7]
The segmental K-means algorithm for estimating parameters of hidden markov models. Juang B H,Rabiner L R. IEEE Transactions on Acoustics Speech and Signal Processing . 1990
[8]
Hidden Markov models using vector linear prediction and discriminative output distributions.In Proceedings of ICASSP, San Francisco, CA, U. Woodland P C. S.A . 1992
[9]
Hidden Markov models with templates as non-stationary states: an application to speechrecognition. Ghitza O,Sondhi M M. Computer Speech and Language . 1993
[10]
Speaker independent isolated word recognizer using dynamic features of speech spectrum. Furui S. IEEE Transactions on Acoustics Speech and Signal Processing . 1981