Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/101329
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
http://hdl.handle.net/10220/16271
DOI: 10.1109/ICALIP.2012.6376652
Fulltext Permission: none
Fulltext Availability: No Fulltext
Appears in Collections:TL Conference Papers

Google ScholarTM

Check

Altmetric

Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.