A study of two dimensional linear discriminants for ASR

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

Volumn 1, Issue , 2001, Pages 137-140

  Kajarekar, Sachin S ^a   Yegnanarayana, B ^c   Hermansky, Hynek ^a,b  

^a OREGON HEALTH AND SCIENCE UNIVERSITY   (United States)

^b INTERNATIONAL COMPUTER SCIENCE INSTITUTE   (United States)

^c INDIAN INSTITUTE OF TECHNOLOGY MADRAS   (India)

Author keywords

[No Author keywords available]

Indexed keywords

JOINT LINEAR DISCRIMINANTS; LINEAR DISCRIMINANT ANALYSIS; TWO DIMENSIONAL LINEAR DISCRIMINANTS;

EIGENVALUES AND EIGENFUNCTIONS; FEATURE EXTRACTION; PRINCIPAL COMPONENT ANALYSIS; PROBABILITY DISTRIBUTIONS; SPECTROGRAPHS; SPEECH ANALYSIS; SPEECH PROCESSING; STATISTICAL METHODS; TWO DIMENSIONAL;

SPEECH RECOGNITION;

EID: 0034853040     PISSN: 15206149     EISSN: None     Source Type: Journal    
DOI: 10.1109/ICASSP.2001.940786     Document Type: Article

References (10)

1. A comparison of several acoustic representations for speech recognition with degraded and undegraded speech
2. Spectral basis functions from discriminant analysis
3. Data-based RASTA-like filter design for channel normalization in ASR
4. Robust methods for using contex-dependent features and models in a continuous speech recognizer
5. Discriminative spectral-temporal multiresolution features for speech recognition
6. A novel feature-extraction for speech recognition based on multiple acoustic-feature planes
7. Analysis of sources of variability in speech
8. Telephone speech corpus development at CSLU