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

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 i...

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Bibliographic Details
Published in:TheScientificWorld 2014-01, Vol.2014 (2014), p.1-12
Main Authors: Ko, Hanseok, Han, David K., Kim, Wooil, Park, Jinsoo
Format: Article
Language:English
Subjects:
Algorithms
Computer engineering
Experiments
Fourier transformations
Fourier transforms
Methods
Models, Theoretical
Noise
Speech
Speech Acoustics
Voice recognition
Wavelet transforms
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Summary: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.
ISSN:2356-6140
1537-744X
1537-744X
DOI:10.1155/2014/146040