음성구간검출을 위한 비정상성 잡음에 강인한 특징 추출 Robust Feature Extraction for Voice Activity Detection in Nonstationary Noisy Environments

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This paper proposes robust feature extraction for accurate voice activity detection (VAD). VAD is one of the principal modules for speech signal processing such as speech codec, speech enhancement, and speech recognition. Noisy environments contain nonstationary noises causing the accuracy of the VAD to drastically decline because the fluctuation of features in the noise intervals results in increased false alarm rates. In this paper, in order to improve the VAD performance, harmonic-weighted energy is proposed. This feature extraction method focuses on voiced speech intervals and weighted harmonic-to-noise ratios to determine the amount of the harmonicity to frame energy. For performance evaluation, the receiver operating characteristic curves and equal error rate are measured.
Publisher
한국음성학회
Issue Date
2013-03
Language
Korean
Citation

말소리와 음성과학, v.5, no.1, pp.11 - 16

ISSN
2005-8063
URI
http://hdl.handle.net/10203/255071
Appears in Collection
EE-Journal Papers(저널논문)
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