Multiple regression of log spectra for in-car speech recognition using multiple distributed microphones

IEICE Transactions on Information and Systems

Volumn E88-D, Issue 3, 2005, Pages 384-389

  Li, Weifeng ^a   Shinde, Tetsuya ^a   Fujimura, Hiroshi ^a   Miyajima, Chiyomi ^a   Nishino, Takanori ^a   Itou, Katunobu ^a   Takeda, Kazuya ^b   Itakura, Fumitad ^b  

^a NAGOYA UNIVERSITY   (Japan)

^b MEIJO UNIVERSITY   (Japan)

Author keywords

Adaptive beamforming; Microphone arrays; Multiple regression; Signal to deviation ratio; Speech recognition

Indexed keywords

COMMUNICATION CHANNELS (INFORMATION THEORY); MICROPHONES; REGRESSION ANALYSIS; SENSITIVITY ANALYSIS; SPEECH PROCESSING; STATISTICAL METHODS;

ADAPTIVE BEAMFORMING; MICROPHONE ARRAYS; MULTIPLE REGRESSION; SIGNAL-TO-DEVIATION RATIO;

SPEECH RECOGNITION;

EID: 24144471130     PISSN: 09168532     EISSN: None     Source Type: Journal    
DOI: 10.1093/ietisy/e88-d.3.384     Document Type: Article

References (16)

1. C. Junqua and P. Haton, Robustness in Automatic Speech Recognition, Kluwer Academic Publishers, 1996.
2. L.J. Griffiths and C.W. Jim, "An alternative approach to linearly constrained adaptive beamforming," IEEE Trans. Antennas Propag., vol.AP-30, no.1, pp.27-34, Jan. 1982.
3. Y. Kaneda and J. Ohga, "Adaptive microphone-array system for noise reduction," IEEE Trans. Acoust. Speech Signal Process., vol.34, no.6, pp.1391-1400, 1986.
4. O. Hoshuyama and A. Sugiyama, "A robust adaptive beamformer for microphone arrays with a blocking matrix using constrained adaptive filters," Proc. IEEE International Conference on Acoustics, Speech, and Signal Processing, pp.925-928, 1996.
5. M. Brandstein and D. Ward, Microphone Arrays: Signal Processing Techniques and Applications, Springer-Verlag, 2001.
6. I. McCowan, D. Moore, and S. Sridharan, "Near-field adaptive beamformer with application to robust speech recognition," Digit. Signal Process.: A Review, vol.12, no.l, pp.87-106, Jan. 2002.
7. Y. Shimizu, S. Kajita, K. Takeda, and F. Itakura, "Speech recognition based on space diversity using distributed multi-microphone," Proc. IEEE International Conference on Acoustics, Speech, and Signal Processing, vol.III, pp.1747-1750, Istanbul, June 2000.
8. S. Young, J. Odeu, D. Ollason, V. Valtchev, and P. Woodland, "The HTK Book," Version 2.1, Cambridge University, 1997.
9. M.L. Seltzer, B. Raj, and R.M. Stern, "Speech recognizer-based microphone array processing for robust hands-free speech recognition," Proc. IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP2002, vol.1, pp.897-900, Orlando, 2002.
10. N. Kawaguchi, S. Matsubara, H. Iwa, S. Kajita, K. Takeda, F. Itakura, and Y. Inagaki, "Construction of speech corpus in moving car environment," Proc. 6th International Conference on Spoken Language Processing, ICSLP2000, pp.362-365, Beijing, China, 2000.
11. X. Zhang and J.H.L. Hansen, "A constrained switched adaptive beamforming for speech enhancement & recognition in real car environments," IEEE. Trans. Speech Audio Process., vol.11, no.6, pp.733-745, Nov. 2003.
12. S. Haykin, Adaptive Filter Theory, Prentice Hall, 2002.
13. H. Fujimura, K. Itou, K. Takeda, and F. Itakura, "In-car speech recognition experiments using a large-scale multi-mode dialogue corpus," Proc. Independent Components Analysis (ICA), vol.IV, pp.2583-2586, 2004.
14. http://julius.sourceforge.jp
15. S. Haykin, Neural Networks - A Comprehensive Foundation, Prentice Hall, 1999.
16. V. Vapnik, The Nature of Statistic Learning Theory, Springer, 1995.