Markov processes on curves for automatic speech recognition

Advances in Neural Information Processing Systems

Volumn , Issue , 1999, Pages 751-757

  Saul, Lawrence ^a   Rahim, Mazin ^a  

^a AT AND T LABS RESEARCH   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

HIDDEN MARKOV MODELS;

ACOUSTIC FEATURES; ARC LENGTH; AUTOMATIC SPEECH RECOGNITION; GEOMETRIC PROPERTIES; NEW JERSEY; PHONETIC TRANSCRIPTIONS; PROBABILISTIC FRAMEWORK; WORD ERROR RATE;

SPEECH RECOGNITION;

EID: 72549084032     PISSN: 10495258     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (7)

1. M. P. do Carmo(1976). Differential Geometry of Curves and Surfaces. Prentice Hall.
2. M. Ostendorf, V. Digalakis, and O. Kimball (1996). From HMMs to segment models: a unified view of stochastic modeling for speech recognition. IEEE Transactions on Acoustics, Speech and Signal Processing, 4:360-378.
3. L. Rabiner and B. Juang (1993). Fundamentals of Speech Recognition. Prentice Hall, Englewood Cliffs, NJ.
4. R. Sachs, M. Tikijian, and E. Roskos (1994). United States English subword speech data. AT&T unpublished report.
5. L. Saul (1998). Automatic segmentation of continuous trajectories with invariance to nonlinear warpings of time. In Proceedings of the Fifteenth International Conference on Machine Learning, 506-514.
6. M. A. Siegler and R. M. Stern (1995). On the effects of speech rate in large vocabulary speech recognition systems. In Proceedings of the 1995 IEEE International Conference on Acoustics, Speech, and Signal Processing, 612-615.
7. N. Tishby (1990). A dynamical system approach to speech processing. In Proceedings of the 1990 IEEE International Conference on Acoustics, Speech, and Signal Processing, 365-368.