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Volumn 2, Issue , 2006, Pages 749-754

Kernel based non-linear feature extraction methods for speech recognition

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; DISCRIMINANT ANALYSIS; FEATURE EXTRACTION; MAXIMUM LIKELIHOOD;

EID: 34547500844     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ISDA.2006.253706     Document Type: Conference Paper
Times cited : (4)

References (15)
  • 3
    • 85017287487 scopus 로고
    • Linear discriminant analysis for improved large vocabulary continuous speech recognition
    • R.Haeb-Umbach, H. Ney, "Linear discriminant analysis for improved large vocabulary continuous speech recognition," Proc. of ICASSP92, vol.1, pp. 13-16,1992.
    • (1992) Proc. of ICASSP92 , vol.1 , pp. 13-16
    • Haeb-Umbach, R.1    Ney, H.2
  • 4
    • 0033677121 scopus 로고    scopus 로고
    • Maximum likelihood discriminant feature spaces,
    • George Saon, Mukund Padmanabhan, Ramesh Gopinath and Scott Chen, "Maximum likelihood discriminant feature spaces, " Proc. of ICASSP2000, vol.2, pp.1129-1132,2000.
    • (2000) Proc. of ICASSP2000 , vol.2 , pp. 1129-1132
    • Saon, G.1    Padmanabhan, M.2    Gopinath, R.3    Chen, S.4
  • 5
    • 0032289099 scopus 로고    scopus 로고
    • Heteroscedastic discriminant analysis and reduced rank HMMs for improved speech recognition
    • N. Kumar, Andreas G. Andreou, "Heteroscedastic discriminant analysis and reduced rank HMMs for improved speech recognition," Speech Communication, vol. 26, pp.283-297, 1998.
    • (1998) Speech Communication , vol.26 , pp. 283-297
    • Kumar, N.1    Andreas, G.2    Andreou3
  • 6
    • 84892187452 scopus 로고    scopus 로고
    • Maximum likelihood modeling withGaussian distributions for classification
    • R.A.Gopinath, "Maximum likelihood modeling withGaussian distributions for classification," Proc. of ICASSP98, vol.2, pp.661-664, 1998.
    • (1998) Proc. of ICASSP98 , vol.2 , pp. 661-664
    • Gopinath, R.A.1
  • 8
    • 0347243182 scopus 로고    scopus 로고
    • Nonlinear component analysis as a kernel eigenvalue problem
    • B. Schölkopf, A. Smola, and K.- R. Müller," Nonlinear component analysis as a kernel eigenvalue problem,"Neural Computation, 10,1299-1319,1998.
    • (1998) Neural Computation , vol.10 , pp. 1299-1319
    • Schölkopf, B.1    Smola, A.2    Müller, K.R.3
  • 10
    • 0034296402 scopus 로고    scopus 로고
    • Generalized discriminant analysis using a kernel approach
    • G.Baudat, and F. Anouar, "Generalized discriminant analysis using a kernel approach", Neural Computation 12, 2385-2404, 2000.
    • (2000) Neural Computation , vol.12 , pp. 2385-2404
    • Baudat, G.1    Anouar, F.2
  • 11
    • 3543105497 scopus 로고    scopus 로고
    • Kernel-based feature extraction with a speech technology application
    • A. Kocsor and L. Tóth, "Kernel-based feature extraction with a speech technology application," IEEE Trans. On Signal Process ing, vol.52, no.8,pp.2250-2263, 2004.
    • (2004) IEEE Trans. On Signal Process ing , vol.52 , Issue.8 , pp. 2250-2263
    • Kocsor, A.1    Tóth, L.2
  • 12
    • 34547507296 scopus 로고    scopus 로고
    • M. G .Genton, Class of kernels for machine learning: A statistics perspective, J. Machine Learning Res,2, pp.299-312, 2001.
    • M. G .Genton, "Class of kernels for machine learning: A statistics perspective," J. Machine Learning Res,vol.2, pp.299-312, 2001.
  • 14
    • 0242383468 scopus 로고    scopus 로고
    • Feature vector selection and projection using kernels
    • G. Baudat, F. Anouar, "Feature vector selection and projection using kernels," Neurocomputing, vol.55, pp 21-38, 2003.
    • (2003) Neurocomputing , vol.55 , pp. 21-38
    • Baudat, G.1    Anouar, F.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.