A dynamic, feature-based approach to the interface between phonology and phonetics for speech modeling and recognition

[1]  Sadaoki Furui.  Flexible speech recognition , 1995, EUROSPEECH.

[2]  Lee A. Feldkamp,et al.  Neurocontrol of nonlinear dynamical systems with Kalman filter trained recurrent networks , 1994, IEEE Trans. Neural Networks.

[3]  P. Denes.  The Speech Chain , 1963 .

[4]  Li Deng,et al.  Computational Models for Speech Production , 2018, Speech Processing.

[5]  Keikichi Hirose,et al.  Analysis of voice fundamental frequency contours for declarative sentences of Japanese , 1984 .

[6]  P. Denes,et al.  The speech chain : the physics and biology of spoken language , 1963 .

[7]  Steven Greenberg,et al.  ON THE ORIGINS OF SPEECH INTELLIGIBILITY IN THE REAL WORLD , 1997 .

[8]  J. Mendel.  Lessons in Estimation Theory for Signal Processing, Communications, and Control , 1995 .

[9]  F. Jelinek,et al.  Continuous speech recognition by statistical methods , 1976, Proceedings of the IEEE.

[10]  Hervé Bourlard,et al.  Connectionist Speech Recognition: A Hybrid Approach , 1993 .

[11]  Kuldip K. Paliwal,et al.  Automatic Speech and Speaker Recognition , 1996 .

[12]  K. M. Ponting,et al.  Computational Models of Speech Pattern Processing , 1999, NATO ASI Series.

[13]  Kenneth N. Stevens,et al.  On the quantal nature of speech , 1972 .

[14]  P. Ladefoged,et al.  The sounds of the world's languages , 1996 .

[15]  L. Deng,et al.  CONTEXT-DEPENDENT MARKOV MODEL STRUCTURED BY LOCUS EQUATIONS : APPLICATIONS TO PHONETIC CLASSIFICATION , 1994 .

[16]  J. R. Rohlicek,et al.  ML estimation of a stochastic linear system with the EM algorithm and its application to speech recognition , 1993, IEEE Trans. Speech Audio Process..

[17]  S. Maeda.  On articulatory and acoustic variabilities , 1991 .

[18]  Philip N. Garner,et al.  Using formant frequencies in speech recognition , 1997, EUROSPEECH.

[19]  K. Stevens,et al.  Feature geometry and the vocal tract , 1994 .

[20]  Li Deng,et al.  Computational Models for Auditory Speech Processing , 1999 .

[21]  Steve J. Young,et al.  Towards improved speech recognition using a speech production model , 1995, EUROSPEECH.

[22]  Kenneth Ward Church.  Phonological parsing in speech recognition , 1987 .

[23]  Stephanie Seneff,et al.  Phonological Parsing for Bi-directional Letter-to-Sound/Sound-to-Letter Generation , 1994, HLT.

[24]  Kuldip K. Paliwal,et al.  Automatic Speech and Speaker Recognition: Advanced Topics , 1999 .

[25]  Norman J. Lass,et al.  Principles of Experimental Phonetics , 1996 .

[26]  Li Deng,et al.  Hierarchical Partitioning of Articulatory State Space for Articulatory-Feature Based Speech Recognition , 1996 .

[27]  L. Deng.  Design of a feature‐based speech recognizer aiming at integration of auditory processing, signal modeling, and phonological structure of speech , 1993 .

[28]  George N. Clements,et al.  The geometry of phonological features , 1985, Phonology Yearbook.

[29]  Mari Ostendorf,et al.  From HMM's to segment models: a unified view of stochastic modeling for speech recognition , 1996, IEEE Trans. Speech Audio Process..

[30]  Hynek Hermansky,et al.  Towards increasing speech recognition error rates , 1995, Speech Commun..

[31]  David J. C. MacKay,et al.  Bayesian Interpolation , 1992, Neural Computation.

[32]  Li Deng,et al.  Integrated-multilingual speech recognition using universal phonological features in a functional speech production model , 1997, 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[33]  G. G. Stokes.  "J." , 1890, The New Yale Book of Quotations.

[34]  Michael I. Jordan,et al.  Goal-based speech motor control: A theoretical framework and some preliminary data , 1995 .

[35]  Ian Maddieson,et al.  Patterns of sounds , 1986 .

[36]  G. Kitagawa.  Non-Gaussian State—Space Modeling of Nonstationary Time Series , 1987 .

[37]  Li Deng,et al.  Transitional speech units and their representation by regressive Markov states: applications to speech recognition , 1996, IEEE Trans. Speech Audio Process..

[38]  New York Dover,et al.  ON THE CONVERGENCE PROPERTIES OF THE EM ALGORITHM , 1983 .

[39]  J. Blevins.  The Syllable in Phonological Theory , 1995 .

[40]  Louis Goldstein,et al.  Towards an articulatory phonology , 1986, Phonology.

[41]  Li Deng,et al.  Speech recognition using the atomic speech units constructed from overlapping articulatory features , 1994, EUROSPEECH.

[42]  Li Deng,et al.  A stochastic model of speech incorporating hierarchical nonstationarity , 1993, IEEE Trans. Speech Audio Process..

[43]  Steven Greenberg,et al.  UNDERSTANDING SPEECH UNDERSTANDING: TOWARDS A UNIFIED THEORY OF SPEECH PERCEPTION , 1996 .

[44]  Wray L. Buntine,et al.  Bayesian Back-Propagation , 1991, Complex Syst..

[45]  Li Deng,et al.  Improved speech modeling and recognition using multi-dimensional articulatory states as primitive speech units , 1995, 1995 International Conference on Acoustics, Speech, and Signal Processing.

[46]  W. Levelt.  Speaking: From Intention to Articulation , 1990 .

[47]  L Saltzman Elliot,et al.  A Dynamical Approach to Gestural Patterning in Speech Production , 1989 .

[48]  Biing-Hwang Juang,et al.  An Overview of Automatic Speech Recognition , 1996 .

[49]  D. Rubin,et al.  Maximum likelihood from incomplete data via the EM - algorithm plus discussions on the paper , 1977 .

[50]  Li Deng,et al.  A generalized hidden Markov model with state-conditioned trend functions of time for the speech signal , 1992, Signal Process..

[51]  Chin-Hui Lee,et al.  A Bayesian predictive classification approach to robust speech recognition , 2000, IEEE Trans. Speech Audio Process..

[52]  Heekuck Oh,et al.  Neural Networks for Pattern Recognition , 1993, Adv. Comput..

[53]  Li Deng,et al.  Production models as a structural basis for automatic speech recognition , 1997, Speech Commun..

[54]  M. E. Welch,et al.  Bayesian analysis of time series and dynamic models , 1990 .

[55]  Xiaodong Sun,et al.  Speech recognition using hidden Markov models with polynomial regression functions as nonstationary states , 1994, IEEE Trans. Speech Audio Process..

[56]  Hossein Sameti,et al.  From Modeling Surface Phenomena to Modeling Mechanisms: Towards a Faithful Model of the Speech Process Aiming at Speech Recognition , 1995 .

[57]  F. Newmeyer.  Linguistics: The Cambridge Survey , 1989 .

[58]  Li Deng,et al.  Optimal filtering and smoothing for speech recognition using a stochastic target model , 1996, Proceeding of Fourth International Conference on Spoken Language Processing. ICSLP '96.