Subband analysis for robust speech recognition in the presence of car noise
Author
Çetin, A. Enis
Yardımcı, Y.
Erzin, Engin
Date
1995-05Source Title
IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 1995
Print ISSN
0736-7791
Publisher
IEEE
Pages
417 - 420
Language
English
Type
Conference PaperItem Usage Stats
148
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120
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Abstract
In this paper, a new set of speech feature representations for robust speech recognition in the presence of car noise are proposed. These parameters are based on subband analysis of the speech signal. Line Spectral Frequency (LSF) representation of the Linear Prediction (LP) analysis in subbands and cepstral coefficients derived from subband analysis (SUBCEP) are introduced, and the performances of the new feature representations are compared to mel scale cepstral coefficients (MELCEP) in the presence of car noise. Subband analysis based parameters are observed to be more robust than the commonly employed MELCEP representations.
Keywords
Acoustic noiseComputer simulation
Feature extraction
Markov processes
Mathematical models
Numerical analysis
Polynomials
Speech analysis
Vector quantization
Parameter estimation
Pattern recognition systems
Performance
Cepstral coefficient
Line spectral frequency
Linear prediction analysis
Mel scale cepstral coefficient
Speech signal
Subband analysis
Car noise
Hidden Markov model
Linear predictive coding
Mel scale cepstral coefficients
Speech recognition system
Speech recognition
Permalink
http://hdl.handle.net/11693/27764Published Version (Please cite this version)
https://doi.org/10.1109/ICASSP.1995.479610Collections
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