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http://dx.doi.org/10.7776/ASK.2013.32.2.147

Robust Speech Endpoint Detection in Noisy Environments for HRI (Human-Robot Interface)  

Park, Jin-Soo (고려대학교 바이오마이크로시스템기술 협동과정)
Ko, Han-Seok (고려대학교 전기전자전파공학부)
Publication Information
The Journal of the Acoustical Society of Korea / v.32, no.2, 2013 , pp. 147-156 More about this Journal
Abstract
In this paper, a new speech endpoint detection method in noisy environments for moving robot platforms is proposed. In the conventional method, the endpoint of speech is obtained by applying an edge detection filter that finds abrupt changes in the feature domain. However, since the feature of the frame energy is unstable in such noisy environments, it is difficult to accurately find the endpoint of speech. Therefore, a novel feature extraction method based on the twice-iterated fast fourier transform (TIFFT) and statistical models of speech is proposed. The proposed feature extraction method was applied to an edge detection filter for effective detection of the endpoint of speech. Representative experiments claim that there was a substantial improvement over the conventional method.
Keywords
Speech segmentation; Log likelihood ratio; Frame energy; Fast fourier transform; Edge detection filter; Spectral pattern;
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