Rathinavelu Chengalvarayan

发表

Use of periodicity and jitter as speech recognition features

David L. Thomson, Rathinavelu Chengalvarayan, R. Chengalvarayan, 1998, Proceedings of the 1998 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '98 (Cat. No.98CH36181).

Umgebungsgeräuscheinkopplung for use in speech recognition

Rathinavelu Chengalvarayan, Timothy J. Grost, 2008 .

A Markov model containing state-conditioned second-order non-stationarity: application to speech recognition

Li Deng, Rathinavelu Chengalvarayan, L. Deng, 1995, Comput. Speech Lang..

Use of vector-valued dynamic weighting coefficients for speech recognition: maximum likelihood approach

Rathinavelu Chengalvarayan, R. Chengalvarayan, 1997, EUROSPEECH.

Influence of outliers in training the parametric trajectory models for speech recognition

Rathinavelu Chengalvarayan, 1997, EUROSPEECH.

Improved speech modelling and recognition using a new training algorithm based on outlier-emphasis for non-stationary state HMM

Rathinavelu Chengalvarayan, R. Chengalvarayan, 1998, Speech Commun..

HMM-based echo and announcement modeling approaches for noise suppression avoiding the problem of false triggers

David L. Thomson, Rathinavelu Chengalvarayan, 2000, INTERSPEECH.

HMM-based speech recognition using state-dependent, discriminatively derived transforms on mel-warped DFT features

Li Deng, Rathinavelu Chengalvarayan, L. Deng, 1997, IEEE Trans. Speech Audio Process..

Unified speech recognition for the landline and wireless environments

Rathinavelu Chengalvarayan, Rafid A. Sukkar, John Jacob, 2002, 2002 IEEE International Conference on Acoustics, Speech, and Signal Processing.

HMM-based speech recognition using state-dependent, linear transforms on Mel-warped DFT features

Rathinavelu Chengalvarayan, Li Deng, 1996, 1996 IEEE International Conference on Acoustics, Speech, and Signal Processing Conference Proceedings.

Maximum-likelihood updates of HMM duration parameters for discriminative continuous speech recognition

Rathinavelu Chengalvarayan, R. Chengalvarayan, 1998, ICSLP.

Integrating multiple pronunciations during MCE-based acoustic model training for large vocabulary speech recognition

Rathinavelu Chengalvarayan, 2002, INTERSPEECH.

The AT&t speech API: a study on practical challenges for customized speech to text service

Andrej Ljolje, David L. Thomson, Rathinavelu Chengalvarayan, 2013, INTERSPEECH.

Speaker adaptation experiments using nonstationary-state hidden Markov models: a MAP approach

Li Deng, Rathinavelu Chengalvarayan, 1997, 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing.

Correcting incomprehensible synthetic speech

Rathinavelu Chengalvarayan, Gaurav Talwar, 2012 .

Speech trajectory discrimination using the minimum classification error learning

Li Deng, Rathinavelu Chengalvarayan, L. Deng, 1998, IEEE Trans. Speech Audio Process..

Discriminatively derived HMM-based announcement modeling approach for noise control avoiding the problem of false alarms

David L. Thomson, Rathinavelu Chengalvarayan, 2000, INTERSPEECH.

Use of generalized dynamic feature parameters for speech recognition: maximum likelihood and minimum classification error approaches

Li Deng, Rathinavelu Chengalvarayan, 1995, 1995 International Conference on Acoustics, Speech, and Signal Processing.

Use of linear extrapolation based linear predictive cepstral features (LE-LPCC) for Tamil speech recognition

Rathinavelu Chengalvarayan, R. Chengalvarayan, 2000, INTERSPEECH.

Minimum classification error linear regression (MCELR) for speaker adaptation using HMM with trend functions

Rathinavelu Chengalvarayan, 1997, EUROSPEECH.

Use of multiple classifiers for speech recognition in wireless CDMA network environments

Rathinavelu Chengalvarayan, R. Chengalvarayan, 2000, INTERSPEECH.

Use of generalized dynamic feature parameters for speech recognition

Li Deng, Rathinavelu Chengalvarayan, L. Deng, 1997, IEEE Trans. Speech Audio Process..

The use of nonlinear energy transformation for Tamil connected-digit speech recognition

Rathinavelu Chengalvarayan, 2000, INTERSPEECH.

Evaluation of front-end features and noise compensation methods for robust Mandarin speech recognition

Rathinavelu Chengalvarayan, R. Chengalvarayan, 2001, INTERSPEECH.

Robust energy normalization using speech/nonspeech discriminator for German connected digit recognition

Rathinavelu Chengalvarayan, R. Chengalvarayan, 1999, EUROSPEECH.

Segmentation Strategies for Streaming Speech Translation

Andrej Ljolje, Srinivas Bangalore, Rathinavelu Chengalvarayan, 2013, HLT-NAACL.

A comparative study of hybrid modelling techniques for improved telephone speech recognition

Rathinavelu Chengalvarayan, R. Chengalvarayan, 1998, ICSLP.

Accent-independent universal HMM-based speech recognizer for american, australian and british English

Rathinavelu Chengalvarayan, 2001, INTERSPEECH.

A maximum a posteriori approach to speaker adaptation using the trended hidden Markov model

Li Deng, Rathinavelu Chengalvarayan, L. Deng, 2001, IEEE Trans. Speech Audio Process..

Adaptation of male acoustic models on the basis of language-independent female voice data

Rathinavelu Chengalvarayan, Gaurav Talwar, 2011 .

Robust HMM training for unified dutch and German speech recognition

Rathinavelu Chengalvarayan, 2002, INTERSPEECH.

Hierarchical subband linear predictive cepstral (HSLPC) features for HMM-based speech recognition

Rathinavelu Chengalvarayan, 1999, 1999 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings. ICASSP99 (Cat. No.99CH36258).

Unified acoustic modeling for continuous speech recognition

Rathinavelu Chengalvarayan, 2000, INTERSPEECH.

Construction of state-dependent dynamic parameters using the maximum likelihood approach: Applications to speech recognition

Li Deng, Rathinavelu Chengalvarayan, L. Deng, 1996, Signal Process..

On the use of matrix derivatives in integrated design of dynamic feature parameters for speech recognition

Rathinavelu Chengalvarayan, 2001, 2001 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.01CH37221).

On the use of normalized LPC error towards better large vocabulary speech recognition systems

Rathinavelu Chengalvarayan, 1998, Proceedings of the 1998 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '98 (Cat. No.98CH36181).

The trended HMM with discriminative training for phonetic classification

Li Deng, Rathinavelu Chengalvarayan, 1996, Proceeding of Fourth International Conference on Spoken Language Processing. ICSLP '96.

Method and apparatus for managing user-name tags for a vehicle communication system

Rathinavelu Chengalvarayan, John J. Correia, 2005 .

Look-ahead sequential feature vector normalization for noisy speech recognition

Rathinavelu Chengalvarayan, 2000, INTERSPEECH.

LOOK-A-HEAD SEQUENTIAL FEATURE VECTOR NORMALIZATION FOR NOISY SPEECH RECOGNITION

Rathinavelu Chengalvarayan, 2000 .