메뉴 건너뛰기




Volumn , Issue , 2008, Pages 4733-4736

Localized spectro-temporal cepstral analysis of speech

Author keywords

Cepstral analysis; Nervous system; Speech processing; Speech recognition

Indexed keywords

CEPSTRAL ANALYSIS; FEATURE ANALYSIS; NERVOUS SYSTEM; SPEECH PROCESSING; SPEECH RECOGNITION;

EID: 51449089975     PISSN: 15206149     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICASSP.2008.4518714     Document Type: Conference Paper
Times cited : (41)

References (16)
  • 3
    • 85009110188 scopus 로고    scopus 로고
    • Learning long-term temporal features in mvcsr using neural networks
    • B. Chen, Q. Zhu, and N. Morgan, "Learning long-term temporal features in mvcsr using neural networks," in Proc. ICSLP, 2004.
    • (2004) Proc. ICSLP
    • Chen, B.1    Zhu, Q.2    Morgan, N.3
  • 5
    • 0032639886 scopus 로고    scopus 로고
    • On the use of support vector machines for phonetic classification
    • P. Clarkson and P.J. Moreno. "On the use of support vector machines for phonetic classification," in Proc. IEEE ICASSP, Vol 2, pp.585-588, 1999.
    • (1999) Proc. IEEE ICASSP , vol.2 , pp. 585-588
    • Clarkson, P.1    Moreno, P.J.2
  • 6
    • 85128407852 scopus 로고    scopus 로고
    • Heterogeneous measurements and multiple classifiers for speech recognition
    • A. Halberstadt and J. Glass. "Heterogeneous measurements and multiple classifiers for speech recognition," in Proc. ICSLP, 1998.
    • (1998) Proc. ICSLP
    • Halberstadt, A.1    Glass, J.2
  • 7
    • 84946730259 scopus 로고    scopus 로고
    • Trap-tandem: Data-driven extraction of temporal features from speech
    • H. Hermansky. "Trap-tandem: Data-driven extraction of temporal features from speech,"in Proc. ASRU Workshop, 2003.
    • (2003) Proc. ASRU Workshop
    • Hermansky, H.1
  • 8
    • 0034853040 scopus 로고    scopus 로고
    • A Study of Two Dimensional Linear Discriminants for ASR
    • Salt Lake City, Utah, USA, May
    • S. Kajarekar, B. Yegnanarayana and H. Hermansky. "A Study of Two Dimensional Linear Discriminants for ASR", in Proc ICASSP, Salt Lake City, Utah, USA, May, 2001.
    • (2001) Proc ICASSP
    • Kajarekar, S.1    Yegnanarayana, B.2    Hermansky, H.3
  • 9
    • 51449111310 scopus 로고
    • Speaker-independent word recognition in noisy environments using dynamic and averaged spectral features based on a two-dimensional mel-cepstrum
    • T. Kitamura, E. Hayahara, and Y. Simazaki, "Speaker-independent word recognition in noisy environments using dynamic and averaged spectral features based on a two-dimensional mel-cepstrum," in Proc. ICSLP, 1990.
    • (1990) Proc. ICSLP
    • Kitamura, T.1    Hayahara, E.2    Simazaki, Y.3
  • 10
    • 85009227802 scopus 로고    scopus 로고
    • Localized spectro-temporal features for automatic speech recognition
    • M. Kleinschmidt, "Localized spectro-temporal features for automatic speech recognition," in Proc. Eurospeech, 2003.
    • (2003) Proc. Eurospeech
    • Kleinschmidt, M.1
  • 11
    • 85009233038 scopus 로고    scopus 로고
    • Improving word accuracy with gabor feature extraction
    • M. Kleinschmidt and D. Gelbart, "Improving word accuracy with gabor feature extraction," in Proc. ICSLP, 2002.
    • (2002) Proc. ICSLP
    • Kleinschmidt, M.1    Gelbart, D.2
  • 12
    • 0002583871 scopus 로고
    • Speech database development: Design and analysis of the acoustic-phonetic corpus
    • L. Lamel, R. Kassel, and S. Seneff. "Speech database development: Design and analysis of the acoustic-phonetic corpus." In Proc. DARPA Speech Rec. Workshop, pp.100-109, 1986.
    • (1986) Proc. DARPA Speech Rec. Workshop , pp. 100-109
    • Lamel, L.1    Kassel, R.2    Seneff, S.3
  • 13
    • 0031187171 scopus 로고    scopus 로고
    • Speech recognition by machines and humans
    • R. P. Lippmann. "Speech recognition by machines and humans", Speech Communication, 22(1), pp.1-15, 1997.
    • (1997) Speech Communication , vol.22 , Issue.1 , pp. 1-15
    • Lippmann, R.P.1
  • 14
    • 0141734591 scopus 로고    scopus 로고
    • Everything Old Is New Again: A Fresh Look at Historical Approaches to Machine Learning
    • Ph.D. thesis, Massachusetts Institute of Technology
    • R. Rifkin. "Everything Old Is New Again: A Fresh Look at Historical Approaches to Machine Learning", Ph.D. thesis, Massachusetts Institute of Technology, 2002.
    • (2002)
    • Rifkin, R.1
  • 15
    • 34547531458 scopus 로고    scopus 로고
    • Noise Robust Phonetic Classification with Linear Regularized Least Squares and Second-Order Features
    • R. Rifkin, K. Schutte, D. Saad, J. Bouvrie, and J. Glass. "Noise Robust Phonetic Classification with Linear Regularized Least Squares and Second-Order Features", in Proc. IEEE ICASSP, 2007.
    • (2007) Proc. IEEE ICASSP
    • Rifkin, R.1    Schutte, K.2    Saad, D.3    Bouvrie, J.4    Glass, J.5
  • 16
    • 0034653816 scopus 로고    scopus 로고
    • Spectral-temporal receptive fields of nonlinear auditory neurons obtained using natural sounds
    • F.E. Theunissen, K. Sen, and A. Doupe, "Spectral-temporal receptive fields of nonlinear auditory neurons obtained using natural sounds," J. Neuro., Vol. 20, pp.2315-2331, 2000.
    • (2000) J. Neuro , vol.20 , pp. 2315-2331
    • Theunissen, F.E.1    Sen, K.2    Doupe, A.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.