A Source-Filter Model-Based Unvoiced Speech Detector for Speech Coding

DOI

10.2991/iccsee.2013.361How to use a DOI?

Keywords

Voice Activity Detection, Generalized Likelihood Ratio Test, Speech Coding, Linear Prediction, Unvoiced Speech Detector

Abstract

A novel and easy to realize approach for Voice Activity Detection (VAD) is proposed based on the source-filter speech model in the application of Linear-Prediction-structure speech coding. Generalized Likelihood Ratio Test (GLRT) is adopted to formulate the voice activity detector which contains an unvoiced speech detector and a voiced speech detector respectively. By exploiting the linear predictive analysis coefficients and the pitch information produced in the speech coder, the two separate detectors work effectively in uncorrelated noise without increasing computational complexity significantly. Experimental results show that the unvoiced speech detector outperforms conventional algorithm used in speech coding under various noisy conditions.

Copyright

© 2013, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Download article (PDF)

TY  - CONF
AU  - Qian Wang
AU  - Xin Du
AU  - Weikang Gu
PY  - 2013/03
DA  - 2013/03
TI  - A Source-Filter Model-Based Unvoiced Speech Detector for Speech Coding
BT  - Proceedings of the 2nd International Conference on Computer Science and Electronics Engineering (ICCSEE 2013)
PB  - Atlantis Press
SP  - 1434
EP  - 1437
SN  - 1951-6851
UR  - https://doi.org/10.2991/iccsee.2013.361
DO  - 10.2991/iccsee.2013.361
ID  - Wang2013/03
ER  -