Discriminative Word-Spotting Using Ordered Spectro-Temporal Patch Features

ITRW on Statistical and Perceptual Audio Processing, SAPA 2008

Volumn , Issue , 2008, Pages 35-40

  Ezzat, Tony ^a   Poggio, Tomaso ^a  

^a MASSACHUSETTS INSTITUTE OF TECHNOLOGY   (United States)

Author keywords

spectro temporal patches; support vector machines; Word spotting

Indexed keywords

ARCHITECTURE;

DETECTION RATES; FALSE POSITIVE; FALSE POSITIVE RATES; FEATURES SETS; NOVEL ARCHITECTURE; SPECTRA'S; SPECTRO-TEMPORAL PATCH; SUPPORT VECTOR MACHINE CLASSIFIERS; SUPPORT VECTORS MACHINE; WORD SPOTTING;

SUPPORT VECTOR MACHINES;

EID: 85063071800     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (11)

1. J.R. Rohlicek, W. Russell, S. Roukos, and H. Gish, "Continuous hidden markov modeling for speaker-independent word spotting," Acoustics, Speech, and Signal Processing, 1989. ICASSP- 89., 1989 International Conference on, pp. 627-630 vol.1, 23-26 May 1989.
2. R.C. Rose and D.B. Paul, "A hidden markov model based keyword recognition system," ICASSP-90, pp. 129-132 vol.1, 3-6 Apr 1990.
3. M. Weintraub, "Keyword-spotting using sri's decipher largevocabulary speech-recognition system," ICASSP-93, vol. 2, pp. 463-466 vol.2, 27-30 Apr 1993.
4. D.A. James and S.J. Young, "A fast lattice-based approach to vocabulary independent wordspotting," ICASSP-94, vol. i, pp. I/377-I/380 vol.1, 19-22 Apr 1994.
5. T. Chih, P. Ru, and S. Shamma, "Multiresolution spectrotemporal analysis of complex sounds," Journal of the Acoustical Society of America, vol. 118, pp. 887-906, 2005.
6. F.E. Theunissen, K. Sen, and A. Doupe, "Spectral-temporal receptive fields of nonlinear auditory neurons obtained using natural sounds," Journal of Neuroscience, vol. 20, pp. 2315-2331, 2000.
7. T. Serre, L. Wolf, S. Bileschi, M. Riesenhuber, and T. Poggio, "Object recognition with cortex-like mechanisms," IEEE Trans. on Pattern Analysis and Machine Intelligence, 2006.
8. M. Riesenhuber and T. Poggio, "Hierachical models of object recognition in cortex," Nature Neuroscience, vol. 2, pp. 1019-1025, 1999.
9. Nello Cristianini and Bernhard Schölkopf, "Support vector machines and kernel methods: the new generation of learning machines," AI Mag., vol. 23, no. 3, pp. 31-41, 2002.
10. A. Halberstadt and J. Glass, "Heterogeneous measurements and multiple classifiers for speech recognition," in Proceedings of ICSLP, 1998.
11. H.G. Hirsch and D.Pearce, "The aurora experimental framework for the performance evaluation of speech recognition systems under noisy conditions," in ASR-2000, pp. 181-188.