Pushing the envelope - aside [speech recognition]
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N. Morgan | Qifeng Zhu | A. Stolcke | K. Sonmez | S. Sivadas | T. Shinozaki | M. Ostendorf | P. Jain | H. Hermansky | D. Ellis | G. Doddington | B. Chen | O. Cretin | H. Bourlard | M. Athineos | H. Bourlard | N. Morgan | D. Ellis | Mari Ostendorf | M. Athineos | H. Hermansky | A. Stolcke | K. Sonmez | S. Sivadas | T. Shinozaki | P. Jain | G. Doddington | B. Chen | O. Cretin
[1] Phil Clendeninn. The Vocoder , 1940, Nature.
[2] O. G. Selfridge,et al. Eyes and Ears for Computers , 1962, Proceedings of the IRE.
[3] H. Dudley. Thirty Years of Vocoder Research , 1964 .
[4] R. Reddy. Eyes and Ears for Computers , 1973 .
[5] 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.
[6] D. Rubin,et al. Maximum likelihood from incomplete data via the EM - algorithm plus discussions on the paper , 1977 .
[7] Sadaoki Furui,et al. Speaker-independent isolated word recognition using dynamic features of speech spectrum , 1986, IEEE Trans. Acoust. Speech Signal Process..
[8] C. Lefebvre,et al. A comparison of several acoustic representations for speech recognition with degraded and undegraded speech , 1989, International Conference on Acoustics, Speech, and Signal Processing,.
[9] Dieter Geller,et al. Improvements in connected digit recognition using linear discriminant analysis and mixture densities , 1993, 1993 IEEE International Conference on Acoustics, Speech, and Signal Processing.
[10] Li Deng,et al. Phonetic classification and recognition using HMM representation of overlapping articulatory features for all classes of English sounds , 1994, Proceedings of ICASSP '94. IEEE International Conference on Acoustics, Speech and Signal Processing.
[11] Hynek Hermansky,et al. RASTA processing of speech , 1994, IEEE Trans. Speech Audio Process..
[12] Steve Renals,et al. IPA: improved phone modelling with recurrent neural networks , 1994, Proceedings of ICASSP '94. IEEE International Conference on Acoustics, Speech and Signal Processing.
[13] Jont B. Allen,et al. How do humans process and recognize speech? , 1994, IEEE Trans. Speech Audio Process..
[14] R. Sternberg,et al. The Road Not Taken , 1994, Journal of learning disabilities.
[15] 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..
[16] Hynek Hermansky,et al. Towards increasing speech recognition error rates , 1995, Speech Commun..
[17] Jeff A. Bilmes,et al. Maximum mutual information based reduction strategies for cross-correlation based joint distributional modeling , 1998, Proceedings of the 1998 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '98 (Cat. No.98CH36181).
[18] James R. Glass,et al. Real-time probabilistic segmentation for segment-based speech recognition , 1998, ICSLP.
[19] Hynek Hermansky,et al. TRAPS - classifiers of temporal patterns , 1998, ICSLP.
[20] Hynek Hermansky,et al. Data-Derived Non-Linear Mapping for Feature Extraction in HMM , 1999 .
[21] Elizabeth Shriberg,et al. Consonant discrimination in elicited and spontaneous speech: a case for signal-adaptive front ends in ASR , 2000, INTERSPEECH.
[22] Sarel van Vuuren,et al. Relevance of time-frequency features for phonetic and speaker-channel classification , 2000, Speech Commun..
[23] David Gelbart,et al. Improving word accuracy with Gabor feature extraction , 2002, INTERSPEECH.
[24] Daniel P. W. Ellis,et al. Frequency-domain linear prediction for temporal features , 2003, 2003 IEEE Workshop on Automatic Speech Recognition and Understanding (IEEE Cat. No.03EX721).
[25] Nelson Morgan,et al. Learning long-term temporal features in LVCSR using neural networks , 2004, INTERSPEECH.
[26] Daniel P. W. Ellis,et al. LP-TRAP: linear predictive temporal patterns , 2004, INTERSPEECH.
[27] Daniel P. W. Ellis,et al. PLP2: Autoregressive modeling of auditory-like 2-D spectro-temporal patterns , 2004 .
[28] PROCEssIng magazInE. IEEE Signal Processing Magazine , 2004 .
[29] Geoffrey Zweig,et al. fMPE: discriminatively trained features for speech recognition , 2005, Proceedings. (ICASSP '05). IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005..
[30] Mari Ostendorf,et al. Multi-rate and variable-rate modeling of speech at phone and syllable time scales [speech recognition applications] , 2005, Proceedings. (ICASSP '05). IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005..