MLP-based factor analysis for tandem speech recognition

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

Volumn , Issue , 2013, Pages 6719-6723

  Ferras, Marc ^a   Bourlard, Herve ^a  

^a IDIAP RESEARCH INSTITUTE   (Switzerland)

Author keywords

factor analysis; multilayer perceptron; neural network; tandem speech recognition

Indexed keywords

LATENT VARIABLE MODELS; MULTI LAYER PERCEPTRON; POSTERIOR PROBABILITY; PROBABILISTIC PRINCIPAL COMPONENT ANALYSIS; SPEAKER VARIABILITY; SPEECH TECHNOLOGY; SUBSPACE GAUSSIAN MIXTURE MODELS; TANDEM SPEECH RECOGNITION;

FACE RECOGNITION; FACTOR ANALYSIS; MULTIVARIANT ANALYSIS; NEURAL NETWORKS; SIGNAL PROCESSING; SPEECH RECOGNITION; TELEPHONE SETS;

TELEPHONE SYSTEMS;

EID: 84890509526     PISSN: 15206149     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICASSP.2013.6638962     Document Type: Conference Paper

References (14)

1. C. M. Bishop, "Latent Variable Models," in Learning in Graphical Models, M. I. Jordan Ed., 1999, pp. 371-403
2. P. Kenny, G. Boulianne, P. Ouellet, and P. Dumouchel, "Joint factor analysis versus eigenchannels in speaker recognition," IEEE Trans. on Audio, Speech and Language Processing, vol. 16, no. 5, pp. 980-988, 2007
3. P. Kenny, P. Ouellet, N. Dehak, V. Gupta, and P. Dumouchel, "A study of inter-speaker variability in speaker verification," IEEE Trans. on Audio, Speech and Language Processing, vol. 15, no. 4, pp. 1435-1447, 2008
4. N. Dehak, R. Dehak, P. Kenny, N Brummer, P. Ouellet, and P. Dumouchel, "Support Vector Machines versus Fast Scoring in the Low-Dimensional Total Variability Space for Speaker Verification," in Proc. INTERSPEECH, 2009, pp. 1559-1562
5. S. J. D. Prince, "Probabilistic Linear Discriminant Analysis for Inferences About Identity," in Proc. IEEE International Conference on Computer Vision, 2007, pp. 1-8
6. P. Kenny, "Bayesian speaker verification with heavytailed priors," in Proc. of the IEEE Speaker Odyssey Workshop, June 2010
7. Dan Povey and Lukas Burget, "The Subspace Gaussian Mixture Model a Structured Model for Speech Recognition," Computer Speech and Language, 2011
8. M. J. F. Gales and S. J. Young, "Multiple-cluster Adaptive Training Schemes," in Proc. IEEE ICASSP, 2001, pp. 361-364
9. P. Kenny, G. Boulianne, and P. Dumouchel, "Eigenvoice modeling with sparse training data," IEEE Trans. on Speech and Audio Processing, vol. 13, no. 3, pp. 345-354, 2005
10. G. Hinton, L. Deng, G. E. Dahl, A. Mohammed, N. Jaitly, A. Senior, V. Vanhoucke, P. Nguyen, T. N. Sainath, and B. Kingsbury, "Deep Neural Networks for Acoustic Modeling in Speech Recognition," IEEE Signal Processing Magazine, vol. 29, pp. 82-97, 2012
11. D.P.W. Ellis, R. Singh, and S. Sivadas, "Tandem acoustic modeling in large-vocabulary recog-nition," in Proc. IEEE ICASSP, 2001, pp. 517-520
12. F. Grezl, M. Karafiat, S. Kontar, and J. Cernocky, "Probabilistic and Bottle-Neck Features for LVCSR of meetings," in Proc. IEEE ICASSP, 2007, pp. 757-760
13. M. A. Kramer, "Nonlinear Principal Component Analysis using Autoassociative Neural Networks," American Institue of Chemical Engineers Journal, vol. 37, pp. 233-243, 1991
14. "Quicknet software," http://www1.icsi. berkeley.edu/Speech/qn. html, Accessed November 25, 2012.