Segment-based Stochastic Modelings for Speech Recognition

[1]  L. R. Rabiner,et al.  Single-frame vowel recognition using vector quantization with several distance measures , 1985, AT&T Technical Journal.

[2]  Ronald W. Schafer,et al.  Digital Processing of Speech Signals , 1978 .

[3]  James L. Flanagan,et al.  Speech processing: An evolving technology , 1986, AT&T Technical Journal.

[4]  Lawrence R. Rabiner,et al.  A tutorial on hidden Markov models and selected applications in speech recognition , 1989, Proc. IEEE.

[5]  Yoshio Yamada,et al.  Bi-gram constraint segment-based speech modeling : An application to the Japanese mono-syllables recognition , 1997 .

[6]  Chin-Hui Lee,et al.  Acoustic modeling for large vocabulary speech recognition , 1990 .

[7]  Sin-Horng Chen,et al.  Generalized minimal distortion segmentation for ANN-based speech recognition , 1995, IEEE Trans. Speech Audio Process..

[8]  Stephen E. Levinson,et al.  Continuously variable duration hidden Markov models for automatic speech recognition , 1986 .

[9]  Lalit R. Bahl,et al.  Experiments with the Tangora 20,000 word speech recognizer , 1987, ICASSP '87. IEEE International Conference on Acoustics, Speech, and Signal Processing.

[10]  B.-H. Juang,et al.  Maximum-likelihood estimation for mixture multivariate stochastic observations of Markov chains , 1985, AT&T Technical Journal.

[11]  A. B. Poritz,et al.  Linear predictive hidden Markov models and the speech signal , 1982, ICASSP.

[12]  Satoshi Takahashi,et al.  Recent Topics in Speech Recognition Research at NTT Laboratories , 1992, HLT.

[13]  Robert M. Gray,et al.  An Improvement of the Minimum Distortion Encoding Algorithm for Vector Quantization , 1985, IEEE Trans. Commun..

[14]  Joseph Picone,et al.  Signal modeling techniques in speech recognition , 1993, Proc. IEEE.

[15]  John E. Markel,et al.  Linear Prediction of Speech , 1976, Communication and Cybernetics.

[16]  L. R. Rabiner,et al.  On the application of vector quantization and hidden Markov models to speaker-independent, isolated word recognition , 1983, The Bell System Technical Journal.

[17]  Hiroaki Sakoe,et al.  A Dynamic Programming Approach to Continuous Speech Recognition , 1971 .

[18]  L. Baum,et al.  An inequality with applications to statistical estimation for probabilistic functions of Markov processes and to a model for ecology , 1967 .

[19]  Hervé Bourlard,et al.  Speech dynamics and recurrent neural networks , 1989, International Conference on Acoustics, Speech, and Signal Processing,.

[20]  L. Baum,et al.  A Maximization Technique Occurring in the Statistical Analysis of Probabilistic Functions of Markov Chains , 1970 .

[21]  Brian Hanson,et al.  Enhancing the discrimination of speaker independent hidden Markov models with corrective training , 1989, International Conference on Acoustics, Speech, and Signal Processing,.

[22]  Frederick Jelinek,et al.  The development of an experimental discrete dictation recognizer , 1985 .

[23]  Biing-Hwang Juang,et al.  Hidden Markov Models for Speech Recognition , 1991 .

[24]  Frank J. Owens Signal processing of speech , 1993 .

[25]  Robert M. Gray,et al.  An Algorithm for Vector Quantizer Design , 1980, IEEE Trans. Commun..

[26]  Torbjørn Svendsen,et al.  On the automatic segmentation of speech signals , 1987, ICASSP '87. IEEE International Conference on Acoustics, Speech, and Signal Processing.

[27]  Kai-Fu Lee Hidden Markov models: past, present, and future , 1989, EUROSPEECH.

[28]  L. Rabiner,et al.  Isolated and Connected Word Recognition - Theory and Selected Applications , 1981, IEEE Transactions on Communications.

[29]  Ian H. Witten Principles of computer speech , 1982 .

[30]  Jr. G. Forney,et al.  The viterbi algorithm , 1973 .

[31]  L. Baum,et al.  An inequality and associated maximization technique in statistical estimation of probabilistic functions of a Markov process , 1972 .

[32]  Biing-Hwang Juang,et al.  Maximum likelihood estimation for multivariate mixture observations of markov chains , 1986, IEEE Trans. Inf. Theory.

[33]  F. Itakura,et al.  Minimum prediction residual principle applied to speech recognition , 1975 .