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The Scientific World Journal
Volume 2014, Article ID 146040, 12 pages
Research Article

Voice Activity Detection in Noisy Environments Based on Double-Combined Fourier Transform and Line Fitting

1Department of Biomicrosystem Technology, Korea University, Anam-dong, Seongbuk-gu, Seoul 136-713, Republic of Korea
2School of Computer Science Engineering, Incheon National University, Songdo-dong, Yeonsu-gu, Incheon 406-772, Republic of Korea
3Office of Naval Research, Arlington, VA 22203, USA
4School of Electrical Engineering, Korea University, Anam-dong, Seongbuk-gu, Seoul 136-713, Republic of Korea

Received 7 February 2014; Revised 4 July 2014; Accepted 10 July 2014; Published 6 August 2014

Academic Editor: Juan Manuel Gorriz Saez

Copyright © 2014 Jinsoo Park et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


A new voice activity detector for noisy environments is proposed. In conventional algorithms, the endpoint of speech is found by applying an edge detection filter that finds the abrupt changing point in a feature domain. However, since the frame energy feature is unstable in noisy environments, it is difficult to accurately find the endpoint of speech. Therefore, a novel feature extraction algorithm based on the double-combined Fourier transform and envelope line fitting is proposed. It is combined with an edge detection filter for effective detection of endpoints. Effectiveness of the proposed algorithm is evaluated and compared to other VAD algorithms using two different databases, which are AURORA 2.0 database and SITEC database. Experimental results show that the proposed algorithm performs well under a variety of noisy conditions.