On the robustness of linear discriminant analysis as a preprocessing step for noisy speech recognition
- 19 November 2002
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- Vol. 1 (15206149) , 125-128
- https://doi.org/10.1109/icassp.1995.479289
Abstract
This paper addresses the problem of speech recognition in a noisy environment by finding a robust speech parametric space. The framework of linear discriminant analysis (LDA) is used to derive an efficient speech parametric space for noisy speech recognition, from a classical static+dynamic MFCC space. We first show that the derived LDA space can lead to a higher discrimination than the MFCC related space, even at low signal-to-noise ratio (SNR). Then, we test the robustness of the LDA space to variations between the training and testing SNR. Experiments are performed on a continuous speech recognition task, where speech is degraded with various noise sources: Gaussian noise, F16, Lynx helicopter, autobus, hair dryer. It was found that LDA is highly sensitive to SNR variations for white noise (Gaussian, hair dryer), while remaining quite efficient for the others.Keywords
This publication has 6 references indexed in Scilit:
- A comparison of several acoustic representations for speech recognition with degraded and undegraded speechPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2003
- Stochastic trajectory modeling for speech recognitionPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002
- Improvements in connected digit recognition using linear discriminant analysis and mixture densitiesPublished by Institute of Electrical and Electronics Engineers (IEEE) ,1993
- Linear discriminant analysis for improved large vocabulary continuous speech recognitionPublished by Institute of Electrical and Electronics Engineers (IEEE) ,1992
- An investigation of PLP and IMELDA acoustic representations and of their potential for combinationPublished by Institute of Electrical and Electronics Engineers (IEEE) ,1991
- Automatic Speaker Recognition Based on Pitch ContoursThe Journal of the Acoustical Society of America, 1972