Towards Robust Distant-Talking Automatic Speech Recognition in Reverberant Environments

[1]  Elmar Nöth,et al.  Maximum likelihood estimation of a reverberation model for robust distant-talking speech recognition , 2007, 2007 15th European Signal Processing Conference.

[2]  Ken'ichi Furuya,et al.  Robust Speech Dereverberation Using Multichannel Blind Deconvolution With Spectral Subtraction , 2007, IEEE Transactions on Audio, Speech, and Language Processing.

[3]  Satoshi Nakamura,et al.  Multichannel Bin-Wise Robust Frequency-Domain Adaptive Filtering and Its Application to Adaptive Beamforming , 2007, IEEE Transactions on Audio, Speech, and Language Processing.

[4]  Walter Kellermann,et al.  A New Concept for Feature-Domain Dereverberation for Robust Distant-Talking ASR , 2007, 2007 IEEE International Conference on Acoustics, Speech and Signal Processing - ICASSP '07.

[5]  Tomohiro Nakatani,et al.  Harmonicity-Based Blind Dereverberation for Single-Channel Speech Signals , 2007, IEEE Transactions on Audio, Speech, and Language Processing.

[6]  Richard M. Stern,et al.  Subband Likelihood-Maximizing Beamforming for Speech Recognition in Reverberant Environments , 2006, IEEE Transactions on Audio, Speech, and Language Processing.

[7]  Walter Kellermann,et al.  Hands-free speech recognition using a reverberation model in the feature domain , 2006, 2006 14th European Signal Processing Conference.

[8]  Biing-Hwang Juang,et al.  Speech Dereverberation Based on Probabilistic Models of Source and Room Acoustics , 2006, 2006 IEEE International Conference on Acoustics Speech and Signal Processing Proceedings.

[9]  Ken'ichi Furuya,et al.  Speech Dereverberation by Combining Mint-Based Blind Deconvolution and Modified Spectral Subtraction , 2006, 2006 IEEE International Conference on Acoustics Speech and Signal Processing Proceedings.

[10]  Shigeki Sagayama,et al.  Model Adaptation for Long Convolutional Distortion by Maximum Likelihood Based State Filtering Approach , 2006, 2006 IEEE International Conference on Acoustics Speech and Signal Processing Proceedings.

[11]  Masafumi Nishimura,et al.  Acoustic Model Adaptation Using First-Order Linear Prediction for Reverberant Speech , 2006, IEICE Trans. Inf. Syst..

[12]  Gerhard Schmidt,et al.  Topics in acoustic echo and noise control : selected methods for the cancellation of acoustical echoes, the reduction of background noise, and speech processing ; with 32 tables , 2006 .

[13]  Hans-Günter Hirsch,et al.  A new HMM adaptation approach for the case of a hands-free speech input in reverberant rooms , 2006, INTERSPEECH.

[14]  Walter Kellermann,et al.  Distant-talking continuous speech recognition based on a novel reverberation model in the feature domain , 2006, INTERSPEECH.

[15]  Elmar Nöth,et al.  Using Artificially Reverberated Training Data in Distant-Talking ASR , 2005, TSD.

[16]  Wolfgang Herbordt.  Sound Capture for Human / Machine Interfaces: Practical Aspects of Microphone Array Signal Processing (Lecture Notes in Control and Information Sciences) , 2005 .

[17]  T. Hikichi,et al.  Blind dereverberation based on estimates of signal transmission channels without precise information on channel order [speech processing applications] , 2005, Proceedings. (ICASSP '05). IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005..

[18]  Tomohiro Nakatani,et al.  Fast estimation of a precise dereverberation filter based on speech harmonicity , 2005, Proceedings. (ICASSP '05). IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005..

[19]  Richard M. Stern,et al.  Likelihood-maximizing beamforming for robust hands-free speech recognition , 2004, IEEE Transactions on Speech and Audio Processing.

[20]  Walter Kellermann,et al.  TRINICON: a versatile framework for multichannel blind signal processing , 2004, 2004 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[21]  David Pallett,et al.  A look at NIST'S benchmark ASR tests: past, present, and future , 2003, 2003 IEEE Workshop on Automatic Speech Recognition and Understanding (IEEE Cat. No.03EX721).

[22]  Tomohiro Nakatani,et al.  Blind dereverberation of single channel speech signal based on harmonic structure , 2003, 2003 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03)..

[23]  Les E. Atlas,et al.  Strategies for improving audible quality and speech recognition accuracy of reverberant speech , 2003, 2003 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03)..

[24]  S. R. Mahadeva Prasanna,et al.  Speech enhancement using excitation source information , 2002, 2002 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[25]  Angelo Farina,et al.  Real-time partitioned convolution for Ambiophonics surround sound , 2001, Proceedings of the 2001 IEEE Workshop on the Applications of Signal Processing to Audio and Acoustics (Cat. No.01TH8575).

[26]  Michael S. Brandstein,et al.  Microphone array speech dereverberation using coarse channel modeling , 2001, 2001 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.01CH37221).

[27]  Alexander Fischer,et al.  Acoustic synthesis of training data for speech recognition in living room environments , 2001, 2001 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.01CH37221).

[28]  Alex Acero,et al.  Spoken Language Processing: A Guide to Theory, Algorithm and System Development , 2001 .

[29]  Satoshi Nakamura,et al.  HMM-separation-based speech recognition for a distant moving speaker , 2001, IEEE Trans. Speech Audio Process..

[30]  Bayya Yegnanarayana,et al.  Enhancement of reverberant speech using LP residual signal , 2000, IEEE Trans. Speech Audio Process..

[31]  Benesty,et al.  Adaptive eigenvalue decomposition algorithm for passive acoustic source localization , 2000, The Journal of the Acoustical Society of America.

[32]  Dimitris G. Manolakis,et al.  Statistical and Adaptive Signal Processing: Spectral Estimation, Signal Modeling, Adaptive Filtering and Array Processing , 1999 .

[33]  Hermann Ney,et al.  Dynamic programming search for continuous speech recognition , 1999, IEEE Signal Process. Mag..

[34]  Gerhard Schmidt,et al.  Acoustic echo control. An application of very-high-order adaptive filters , 1999, IEEE Signal Process. Mag..

[35]  Maurizio Omologo,et al.  Training of HMM with filtered speech material for hands-free recognition , 1999, 1999 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings. ICASSP99 (Cat. No.99CH36258).

[36]  Christina Breining.  Acoustic echo control , 1999 .

[37]  Qiang Hou,et al.  Model adaptation based on HMM decomposition for reverberant speech recognition , 1997, 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[38]  Maurizio Omologo,et al.  Microphone array based speech recognition with different talker-array positions , 1997, 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[39]  Frederick Jelinek,et al.  Statistical methods for speech recognition , 1997 .

[40]  Mark J. F. Gales,et al.  Robust continuous speech recognition using parallel model combination , 1996, IEEE Trans. Speech Audio Process..

[41]  Satoshi Nakamura,et al.  Noise and room acoustics distorted speech recognition by HMM composition , 1996, 1996 IEEE International Conference on Acoustics, Speech, and Signal Processing Conference Proceedings.

[42]  Richard M. Stern,et al.  A vector Taylor series approach for environment-independent speech recognition , 1996, 1996 IEEE International Conference on Acoustics, Speech, and Signal Processing Conference Proceedings.

[43]  Mark J. F. Gales,et al.  Improving environmental robustness in large vocabulary speech recognition , 1996, 1996 IEEE International Conference on Acoustics, Speech, and Signal Processing Conference Proceedings.

[44]  Jean-Claude Junqua,et al.  Robustness in Automatic Speech Recognition , 1996 .

[45]  W. Putnam,et al.  A numerical investigation of the invertibility of room transfer functions , 1995, Proceedings of 1995 Workshop on Applications of Signal Processing to Audio and Accoustics.

[46]  Chrysostomos L. Nikias,et al.  EVAM: an eigenvector-based algorithm for multichannel blind deconvolution of input colored signals , 1995, IEEE Trans. Signal Process..

[47]  Tat Soon Yeo,et al.  Radiation characteristics of coplanar waveguide antenna array , 1994, Proceedings of ICCS '94.

[48]  Hynek Hermansky,et al.  RASTA processing of speech , 1994, IEEE Trans. Speech Audio Process..

[49]  Philip C. Woodland,et al.  Speaker adaptation of continuous density HMMs using multivariate linear regression , 1994, ICSLP.

[50]  Jonathan G. Fiscus,et al.  1993 Benchmark Tests for the ARPA Spoken Language Program , 1994, HLT.

[51]  John G. Proakis,et al.  Digital Signal Processing: Principles, Algorithms, and Applications , 1992 .

[52]  Jia-Sien Soo,et al.  A multistep size (MSS) frequency domain adaptive filter , 1991, IEEE Trans. Signal Process..

[53]  Brian Hanson,et al.  Robust speaker-independent word recognition using static, dynamic and acceleration features: experiments with Lombard and noisy speech , 1990, International Conference on Acoustics, Speech, and Signal Processing.

[54]  Chin-Hui Lee,et al.  A study on speaker adaptation of continuous density HMM parameters , 1990, International Conference on Acoustics, Speech, and Signal Processing.

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

[56]  J.-S. Soo,et al.  Multidelay block frequency domain adaptive filter , 1990, IEEE Trans. Acoust. Speech Signal Process..

[57]  Steve Young,et al.  Token passing: a simple conceptual model for connected speech recognition systems , 1989 .

[58]  Lawrence R. Rabiner,et al.  A tutorial on hidden Markov models and selected applications in speech recognition , 1989, Proc. IEEE.

[59]  Piet Sommen.  Partitioned frequency domain adaptive filters , 1989, Twenty-Third Asilomar Conference on Signals, Systems and Computers, 1989..

[60]  B.D. Van Veen,et al.  Beamforming: a versatile approach to spatial filtering , 1988, IEEE ASSP Magazine.

[61]  Masato Miyoshi,et al.  Inverse filtering of room acoustics , 1988, IEEE Trans. Acoust. Speech Signal Process..

[62]  S. Furui.  On the role of spectral transition for speech perception. , 1986, The Journal of the Acoustical Society of America.

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

[64]  L. J. Griffiths,et al.  An alternative approach to linearly constrained adaptive beamforming , 1982 .

[65]  Stan Davis,et al.  Comparison of Parametric Representations for Monosyllabic Word Recognition in Continuously Spoken Se , 1980 .

[66]  Jont B. Allen,et al.  Invertibility of a room impulse response , 1979 .

[67]  Jont B. Allen,et al.  Image method for efficiently simulating small‐room acoustics , 1976 .

[68]  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.

[69]  Heinrich Kuttruff,et al.  Room acoustics , 1973 .

[70]  L. Baum,et al.  A Maximization Technique Occurring in the Statistical Analysis of Probabilistic Functions of Markov Chains , 1970 .

[71]  L. Baum,et al.  An inequality with applications to statistical estimation for probabilistic functions of Markov processes and to a model for ecology , 1967 .

[72]  Thomas G. Stockham,et al.  High-speed convolution and correlation , 1966, AFIPS '66 (Spring).