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dc.contributor.authorKhoa, Pham Chauen
dc.contributor.authorSiong, Chng Engen
dc.identifier.citationKhoa, P. C., & Siong, C. E. (2012). Spectral local harmonicity feature for voice activity detection. 2012 International Conference on Audio, Language and Image Processing (ICALIP).en
dc.description.abstractIn this paper, we propose a method to exploit the harmonicity of human voiced speech using only the most harmonic sub-part of the spectrum. This technique searches for all the potential sub-windows of the spectrum, and measures their local harmonicity, using a newly proposed metric, which works in the spectral autocorrelation domain and employs a novel sinusoidal fitting approach. Experiments show that the new feature can be used to detect noisy voiced speech frames heavily corrupted by non-stationary noise even at 0dB SNR with high precision and recall, which gives better results than the Windowed Autocorrelation Lag Energy (WALE), a recently proposed voicing features, under a complex factory noise scenarios.en
dc.subjectDRNTU::Engineering::Computer science and engineeringen
dc.titleSpectral local harmonicity feature for voice activity detectionen
dc.typeConference Paperen
dc.contributor.schoolSchool of Computer Engineeringen
dc.contributor.conferenceInternational Conference on Audio, Language and Image Processing (2012 : Shanghai, China)en
dc.contributor.researchTemasek Laboratoriesen
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