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|Title:||Spectral local harmonicity feature for voice activity detection||Authors:||Khoa, Pham Chau
Siong, Chng Eng
|Keywords:||DRNTU::Engineering::Computer science and engineering||Issue Date:||2012||Source:||Khoa, P. C., & Siong, C. E. (2012). Spectral local harmonicity feature for voice activity detection. 2012 International Conference on Audio, Language and Image Processing (ICALIP).||Abstract:||In 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.||URI:||https://hdl.handle.net/10356/101329
|DOI:||10.1109/ICALIP.2012.6376652||Fulltext Permission:||none||Fulltext Availability:||No Fulltext|
|Appears in Collections:||TL Conference Papers|
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