Data-driven temporal filters based on multi-eigenvectors for robust features in speech recognition

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

Volumn 1, Issue , 2003, Pages 400-403

  Wang, Ni Chun ^a   Hung, Jeih Weih ^a   Lee, Lin Shan ^a  

^a NONE

Author keywords

[No Author keywords available]

Indexed keywords

DATABASE SYSTEMS; EIGENVALUES AND EIGENFUNCTIONS; PRINCIPAL COMPONENT ANALYSIS; VECTORS;

TEMPORAL FILTERS;

SPEECH RECOGNITION;

EID: 0141591494     PISSN: 15206149     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (8)

1. J-W. Hung, et al Comparative Analysis for Data-Driven Temporal Filters Obtained Via Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) In Speech Recognition", Eurospeech 2001
2. J-W. Hung and L-S. Lee "Data-Driven Temporal Filters Obtained Via Different Optimization Criteria Evaluated On AURORA2 Database", ICSLP 2002
3. S. Furui, "Cepstral analysis technique for automatic speaker verification". IEEE Trans. Acoust. Speech Signal Process. 1981
4. O. Viikki and K. Laurila, "Noise robust HMM-based speech recognition using segmental cepstral feature vector normalization," in ESCA NATO Workshop Robust Speech Recognition Unknown Communication Channels, Pont-a-Mousson, France, 1997, pp. 107-110.
5. H. Hermansky and N. Morgan, "RASTA processing of speech". IEEE Trans. Speech Audio Process. 2, 578-589, 1994
6. C. Avendano, S. van Vuuren and H. Hermansky, "Data Based Filter Design for RASTA-like Channel Normalization in ASR" ICSLP 96
7. S. van Vuuren and H. Hermansky, "Data-driven Design of RASTA-like Filters", Eurospeech 97
8. nd, Academic Press, 1990