Enhancing the magnitude spectrum of speech features for robust speech recognition

[1]  Jeih-Weih Hung,et al.  Magnitude spectrum enhancement for robust speech recognition , 2010, 2010 IEEE International Conference on Acoustics, Speech and Signal Processing.

[2]  Hoirin Kim,et al.  Histogram Equalization to Model Adaptation for Robust Speech Recognition , 2010, EURASIP J. Adv. Signal Process..

[3]  Jun Du,et al.  Cepstral shape normalization (CSN) for robust speech recognition , 2008, 2008 IEEE International Conference on Acoustics, Speech and Signal Processing.

[4]  Hermann Ney,et al.  Quantile based histogram equalization for noise robust large vocabulary speech recognition , 2006, IEEE Transactions on Audio, Speech, and Language Processing.

[5]  Douglas D. O'Shaughnessy,et al.  Log-energy dynamic range normalization for robust speech recognition , 2005, Proceedings. (ICASSP '05). IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005..

[6]  Tai-Hwei Hwang,et al.  Energy contour enhancement for noisy speech recognition , 2004, 2004 International Symposium on Chinese Spoken Language Processing.

[7]  Naoya Wada,et al.  Cepstral gain normalization for noise robust speech recognition , 2004, 2004 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[8]  Shu Hung Leung,et al.  SNR-dependent non-uniform spectral compression for noisy speech recognition , 2004, 2004 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[9]  Philipos C. Loizou,et al.  A multi-band spectral subtraction method for enhancing speech corrupted by colored noise , 2002, 2002 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[10]  Li Deng,et al.  Evaluation of the SPLICE algorithm on the Aurora2 database , 2001, INTERSPEECH.

[11]  Li Deng,et al.  High-performance robust speech recognition using stereo training data , 2001, 2001 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.01CH37221).

[12]  David Pearce,et al.  The aurora experimental framework for the performance evaluation of speech recognition systems under noisy conditions , 2000, INTERSPEECH.

[13]  Li Deng,et al.  HMM adaptation using vector taylor series for noisy speech recognition , 2000, INTERSPEECH.

[14]  Chin-Hui Lee,et al.  On stochastic feature and model compensation approaches to robust speech recognition , 1998, Speech Commun..

[15]  Richard M. Stern,et al.  Data-driven environmental compensation for speech recognition: A unified approach , 1998, Speech Commun..

[16]  Hynek Hermansky,et al.  Multi-band and adaptation approaches to robust speech recognition , 1997, EUROSPEECH.

[17]  Pascal Scalart,et al.  Speech enhancement based on a priori signal to noise estimation , 1996, 1996 IEEE International Conference on Acoustics, Speech, and Signal Processing Conference Proceedings.

[18]  Chin-Hui Lee,et al.  A maximum-likelihood approach to stochastic matching for robust speech recognition , 1996, IEEE Trans. Speech Audio Process..

[19]  Mark J. F. Gales,et al.  Robust speech recognition in additive and convolutional noise using parallel model combination , 1995, Comput. Speech Lang..

[20]  Mark J. F. Gales,et al.  A fast and flexible implementation of parallel model combination , 1995, 1995 International Conference on Acoustics, Speech, and Signal Processing.

[21]  Philip C. Woodland,et al.  Maximum likelihood linear regression for speaker adaptation of continuous density hidden Markov models , 1995, Comput. Speech Lang..

[22]  Mark J. F. Gales,et al.  Cepstral parameter compensation for HMM recognition in noise , 1993, Speech Commun..

[23]  Alejandro Acero,et al.  Acoustical and environmental robustness in automatic speech recognition , 1991 .

[24]  Roger K. Moore,et al.  Hidden Markov model decomposition of speech and noise , 1990, International Conference on Acoustics, Speech, and Signal Processing.

[25]  A. Nadas,et al.  Speech recognition using noise-adaptive prototypes , 1988, ICASSP-88., International Conference on Acoustics, Speech, and Signal Processing.

[26]  N. Sedgwick,et al.  Noise compensation for speech recognition using probabilistic models , 1986, ICASSP '86. IEEE International Conference on Acoustics, Speech, and Signal Processing.

[27]  David Malah,et al.  Speech enhancement using a minimum mean-square error log-spectral amplitude estimator , 1984, IEEE Trans. Acoust. Speech Signal Process..

[28]  Richard M. Schwartz,et al.  Enhancement of speech corrupted by acoustic noise , 1979, ICASSP.

[29]  S. Boll,et al.  Suppression of acoustic noise in speech using spectral subtraction , 1979 .

[30]  Dennis H. Klatt,et al.  A digital filter bank for spectral matching , 1976, ICASSP.

[31]  B. Atal.  Effectiveness of linear prediction characteristics of the speech wave for automatic speaker identification and verification. , 1974, The Journal of the Acoustical Society of America.

[32]  G. Turin,et al.  An introduction to matched filters , 1960, IRE Trans. Inf. Theory.

[33]  Hossein Sameti,et al.  Likelihood-Maximizing-Based Multiband Spectral Subtraction for Robust Speech Recognition , 2009, EURASIP J. Adv. Signal Process..

[34]  Jeih-Weih Hung,et al.  Silence feature normalization for robust speech recognition in additive noise environments , 2008, INTERSPEECH.

[35]  Jeff A. Bilmes,et al.  MVA Processing of Speech Features , 2007, IEEE Transactions on Audio, Speech, and Language Processing.

[36]  Gang Wei,et al.  Model Compensation Approach Based on Nonuniform Spectral Compression Features for Noisy Speech Recognition , 2007, EURASIP J. Adv. Signal Process..

[37]  P. Scalart,et al.  Improved Signal-to-Noise Ratio Estimation for Speech Enhancement , 2006, IEEE Trans. Speech Audio Process..

[38]  Ephraim.  Speech enhancement using a minimum mean square error short-time spectral amplitude estimator , 1984 .

[39]  S. Haykin.  Communication Systems , 1978 .