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Speech recognition in a noisy car environment based on LP of the one-sided autocorrelation sequence and robust similarity measuring techniques

Author
Hernando, J.; Nadeu, C.; Mariño, J.B.
Type of activity
Journal article
Journal
Speech communication
Date of publication
1997-02
Volume
21
Number
1-2
First page
17
Last page
31
DOI
https://doi.org/10.1016/S0167-6393(96)00074-X Open in new window
Repository
http://hdl.handle.net/2117/97885 Open in new window
URL
http://www.sciencedirect.com/science/article/pii/S016763939600074X Open in new window
Abstract
The performance of the existing speech recognition systems degrades rapidly in the presence of background noise. A novel representation of the speech signal, which is based on Linear Prediction of the One-Sided Autocorrelation sequence (OSALPC), has shown to be attractive for noisy speech recognition because of both its high recognition performance with respect to the conventional LPC in severe conditions of additive white noise and its computational simplicity. The aim of this work is twofold: ...
Citation
Hernando, J., Nadeu, C., Mariño, J.B. Speech recognition in a noisy car environment based on LP of the one-sided autocorrelation sequence and robust similarity measuring techniques. "Speech communication", Febrer 1997, vol. 21, núm. 1-2, p. 17-31.
Keywords
Distortion measures, Feature extraction, Noise robustness, Spectral analysis of speech, Speech recognition, Vector quantization
Group of research
IDEAI-UPC - Intelligent Data Science and Artificial Intelligence Research Center
TALP - Centre for Language and Speech Technologies and Applications
VEU - Speech Processing Group