Robust automatic speech recognition with missing and unreliable acoustic data

[1]  G. A. Miller,et al.  The Intelligibility of Interrupted Speech , 1948 .

[2]  Harvey b. Fletcher,et al.  Speech and hearing in communication , 1953 .

[3]  D. F. Morrison,et al.  Multivariate Statistical Methods , 1968 .

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

[5]  E. Owens Introduction to the Psychology of Hearing , 1977 .

[6]  J. Jenkins,et al.  Dynamic specification of coarticulated vowels. , 1983, The Journal of the Acoustical Society of America.

[7]  R. G. Leonard,et al.  A database for speaker-independent digit recognition , 1984, ICASSP.

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

[9]  Roger K. Moore,et al.  Noise compensation algorithms for use with hidden Markov model based speech recognition , 1988, ICASSP-88., International Conference on Acoustics, Speech, and Signal Processing.

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

[11]  H.J.M. Steeneken,et al.  On measuring and predicting speech intelligibility , 1992 .

[12]  Volker Tresp,et al.  Some Solutions to the Missing Feature Problem in Vision , 1992, NIPS.

[13]  S. Hanson,et al.  Some Solutions to the Missing Feature Problem in Vision , 1993 .

[14]  Michael I. Jordan,et al.  Supervised learning from incomplete data via an EM approach , 1993, NIPS.

[15]  Martin Cooke,et al.  Modelling auditory processing and organisation , 1993, Distinguished dissertations in computer science.

[16]  Mark J. F. Gales,et al.  HMM recognition in noise using parallel model combination , 1993, EUROSPEECH.

[17]  Rainer Martin,et al.  An efficient algorithm to estimate the instantaneous SNR of speech signals , 1993, EUROSPEECH.

[18]  Phil D. Green,et al.  Handling missing data in speech recognition , 1994, ICSLP.

[19]  Guy J. Brown,et al.  Computational auditory scene analysis , 1994, Comput. Speech Lang..

[20]  Pierre Comon,et al.  Independent component analysis, A new concept? , 1994, Signal Process..

[21]  Jont B. Allen,et al.  How do humans process and recognize speech? , 1993, IEEE Trans. Speech Audio Process..

[22]  Terrence J. Sejnowski,et al.  An Information-Maximization Approach to Blind Separation and Blind Deconvolution , 1995, Neural Computation.

[23]  Hans-Günter Hirsch,et al.  Noise estimation techniques for robust speech recognition , 1995, 1995 International Conference on Acoustics, Speech, and Signal Processing.

[24]  C. J. Darwin,et al.  Chapter 11 – Auditory Grouping , 1995 .

[25]  R. M. Warren,et al.  Spectral redundancy: Intelligibility of sentences heard through narrow spectral slits , 1995, Perception & psychophysics.

[26]  Yifan Gong,et al.  Speech recognition in noisy environments: A survey , 1995, Speech Commun..

[27]  Richard Lippmann,et al.  Accurate consonant perception without mid-frequency speech energy , 1996, IEEE Trans. Speech Audio Process..

[28]  Daniel Patrick Whittlesey Ellis,et al.  Prediction-driven computational auditory scene analysis , 1996 .

[29]  Hervé Bourlard,et al.  A mew ASR approach based on independent processing and recombination of partial frequency bands , 1996, Proceeding of Fourth International Conference on Spoken Language Processing. ICSLP '96.

[30]  Misha Pavel,et al.  Towards ASR on partially corrupted speech , 1996, Proceeding of Fourth International Conference on Spoken Language Processing. ICSLP '96.

[31]  Guy J. Brown,et al.  ARE NEURAL OSCILLATIONS THE SUBSTRATE OF AUDITORY GROUPING , 1996 .

[32]  Richard Lippmann,et al.  Speech recognition by machines and humans , 1997, Speech Commun..

[33]  Richard Lippmann,et al.  Using missing feature theory to actively select features for robust speech recognition with interruptions, filtering and noise KN-37 , 1997, EUROSPEECH.

[34]  Guy J. Brown,et al.  Modelling the perceptual segregation of double vowels with a network of neural oscillators , 1997, Neural Networks.

[35]  Phil D. Green,et al.  Missing data techniques for robust speech recognition , 1997, 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[36]  Jon Barker,et al.  Modelling the recognition of spectrally reduced speech , 1997, EUROSPEECH.

[37]  Biing-Hwang Juang,et al.  Filtering the time sequences of spectral parameters for speech recognition, , 1997, Speech Commun..

[38]  Simon King,et al.  Proc. Eurospeech'97 , 1997 .

[39]  Børge Lindberg,et al.  Noise robust recognition using feature selective modeling , 1997, EUROSPEECH.

[40]  Richard M. Stern,et al.  Inference of missing spectrographic features for robust speech recognition , 1998, ICSLP.

[41]  Andrzej Drygajlo,et al.  Speaker verification in noisy environments with combined spectral subtraction and missing feature theory , 1998, Proceedings of the 1998 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '98 (Cat. No.98CH36181).

[42]  Hynek Hermansky,et al.  Should recognizers have ears? , 1998, Speech Commun..

[43]  Phil D. Green,et al.  Some solution to the missing feature problem in data classification, with application to noise robust ASR , 1998, Proceedings of the 1998 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '98 (Cat. No.98CH36181).

[44]  Jon Barker,et al.  Is the sine-wave speech cocktail party worth attending? , 1999, Speech Commun..

[45]  Hervé Bourlard,et al.  The full combination sub-bands approach to noise robust HMM/ANN based ASR , 1999, EUROSPEECH.

[46]  Phil D. Green,et al.  Missing data theory, spectral subtraction and signal-to-noise estimation for robust ASR: an integrated study , 1999, EUROSPEECH.

[47]  Hideki Kawahara,et al.  Missing-data model of vowel identification. , 1999, The Journal of the Acoustical Society of America.

[48]  Bert Cranen,et al.  MISSING FEATURE THEORY IN ASR: MAKE SURE YOU MISS THE RIGHT TYPE OF FEATURES , 1999 .

[49]  Stuart Cunningham,et al.  THE ROLE OF EVIDENCE AND COUNTER-EVIDENCEIN SPEECH PERCEPTION , 1999 .

[50]  Miguel Á. Carreira-Perpiñán,et al.  Mode-Finding for Mixtures of Gaussian Distributions , 2000, IEEE Trans. Pattern Anal. Mach. Intell..

[51]  E. Oja,et al.  Independent Component Analysis , 2013 .

[52]  Francis Jack Smith,et al.  Union: A new approach for combining sub-band observations for noisy speech recognition , 2001, Speech Commun..

[53]  A. Bregman Auditory Scene Analysis , 2001 .

[54]  A. B.,et al.  SPEECH COMMUNICATION , 2001 .