Noise robust speech recognition with a switching linear dynamic model

ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings

Volumn 1, Issue , 2004, Pages

  Droppo, Jasha ^a   Acero, Alex ^a  

^a MICROSOFT RESEARCH   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ACOUSTIC NOISE; APPROXIMATION THEORY; ERROR ANALYSIS; MARKOV PROCESSES; MATHEMATICAL MODELS; PARAMETER ESTIMATION; SWITCHING;

ERROR RATES; HIDDEN MARKOV MODELS (HMM); LINEAR DYNAMIC MODELS (LDM); STATE SEQUENCES;

SPEECH RECOGNITION;

EID: 4544236840     PISSN: 15206149     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (8)

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2. R. Singh and B. Raj, "Tracking noise via dynamical systems with a continuum of states," in Proc. ICASSP, 2003, vol. I, pp. 396-399.
3. J. Droppo, L. Deng, and A. Acero, "A comparison of three non-linear observation models for noisy speech features," in Proc. 2003 Eurospeech, Geneva, Switzerland, September 2003, pp. 681-684.
4. P. Moreno, Speech Recognition in Noisy Environments, Ph.D. thesis, Carnegie Mellon University, 1996.
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6. V. Stouten, H. Van hamme, K. Demuynck, and P. Wambacq, "Robust speech recognition using model-based feature enhancement," in Proc. 2003 Eurospeech, Geneva, Switzerland, September 2003, pp. 17-20.
7. J. Droppo, A. Acero, and L. Deng, "Uncertainty decoding with SPLICE for noise robust speech recognition," in Proc. 2002 ICASSP, Orlando, Florida, May 2002.
8. H. G. Hirsch and D. Pearce, "The AURORA experimental framework for the performance evaluations of speech recognition systems under noisy condidions," in ISCA ITRW ASR2000 "Automatic Speech Recognition: Challenges for the Next Millennium", Paris, France, September 2000.