Robust Speech Features Based on LPC Using Weighted Arcsin Transform
Summary :
To increase the discriminating ability of the speech feature based on linear predictive coding (LPC) and increase its noise robustness, an SNR-dependent arcsin transform is applied to the autocorrelation sequence (ACS) of each analysis frame in a speech signal. Moreover, each component in the ACS is also weighted by the normalized reciprocal of the average magnitude difference function (AMDF) for emphasizing its peak structure. Experimental results for the task of Mandarin digit recognition indicate that the LPC speech feature employing the proposed scheme is more robust than some widely used LPC-based approaches over a wide range of SNR values.
- Publication
- IEICE TRANSACTIONS on Information Vol.E86-D No.2 pp.340-343
- Publication Date
- 2003/02/01
- Publicized
- Online ISSN
- DOI
- Type of Manuscript
- LETTER
- Category
- Speech and Hearing
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Wei-Wen HUNG, "Robust Speech Features Based on LPC Using Weighted Arcsin Transform" in IEICE TRANSACTIONS on Information,
vol. E86-D, no. 2, pp. 340-343, February 2003, doi: .
Abstract: To increase the discriminating ability of the speech feature based on linear predictive coding (LPC) and increase its noise robustness, an SNR-dependent arcsin transform is applied to the autocorrelation sequence (ACS) of each analysis frame in a speech signal. Moreover, each component in the ACS is also weighted by the normalized reciprocal of the average magnitude difference function (AMDF) for emphasizing its peak structure. Experimental results for the task of Mandarin digit recognition indicate that the LPC speech feature employing the proposed scheme is more robust than some widely used LPC-based approaches over a wide range of SNR values.
URL: https://global.ieice.org/en_transactions/information/10.1587/e86-d_2_340/_p
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@ARTICLE{e86-d_2_340,
author={Wei-Wen HUNG, },
journal={IEICE TRANSACTIONS on Information},
title={Robust Speech Features Based on LPC Using Weighted Arcsin Transform},
year={2003},
volume={E86-D},
number={2},
pages={340-343},
abstract={To increase the discriminating ability of the speech feature based on linear predictive coding (LPC) and increase its noise robustness, an SNR-dependent arcsin transform is applied to the autocorrelation sequence (ACS) of each analysis frame in a speech signal. Moreover, each component in the ACS is also weighted by the normalized reciprocal of the average magnitude difference function (AMDF) for emphasizing its peak structure. Experimental results for the task of Mandarin digit recognition indicate that the LPC speech feature employing the proposed scheme is more robust than some widely used LPC-based approaches over a wide range of SNR values.},
keywords={},
doi={},
ISSN={},
month={February},}
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TY - JOUR
TI - Robust Speech Features Based on LPC Using Weighted Arcsin Transform
T2 - IEICE TRANSACTIONS on Information
SP - 340
EP - 343
AU - Wei-Wen HUNG
PY - 2003
DO -
JO - IEICE TRANSACTIONS on Information
SN -
VL - E86-D
IS - 2
JA - IEICE TRANSACTIONS on Information
Y1 - February 2003
AB - To increase the discriminating ability of the speech feature based on linear predictive coding (LPC) and increase its noise robustness, an SNR-dependent arcsin transform is applied to the autocorrelation sequence (ACS) of each analysis frame in a speech signal. Moreover, each component in the ACS is also weighted by the normalized reciprocal of the average magnitude difference function (AMDF) for emphasizing its peak structure. Experimental results for the task of Mandarin digit recognition indicate that the LPC speech feature employing the proposed scheme is more robust than some widely used LPC-based approaches over a wide range of SNR values.
ER -
English
