A simple but efficient voice activity detection algorithm through Hilbert transform and dynamic threshold for speech pathologies

20th Argentinean Bioengineering Society Congress

物理学;生物科学

Ortiz, P.D.^1 ; Villa, Luisa F.^1 ; Salazar, Carlos^1 ; Quintero, O.L.^1

Mathematical Modeling Research Group, GRIMMAT, School of Sciences, Universidad EAFIT, Medellin, Colombia^1

关键词: Artificial noise;    Convex combinations;    Dynamic threshold;    Hilbert transform;    Monophonic signals;    Non-ideal conditions;    Voice activity detection algorithms;    Voice activity detectors;   

Others  :  https://iopscience.iop.org/article/10.1088/1742-6596/705/1/012037/pdf
DOI  :  10.1088/1742-6596/705/1/012037

学科分类：生物科学（综合）

来源: IOP

【 摘 要 】

A simple but efficient voice activity detector based on the Hilbert transform and a dynamic threshold is presented to be used on the pre-processing of audio signals. The algorithm to define the dynamic threshold is a modification of a convex combination found in literature. This scheme allows the detection of prosodic and silence segments on a speech in presence of non-ideal conditions like a spectral overlapped noise. The present work shows preliminary results over a database built with some political speech. The tests were performed adding artificial noise to natural noises over the audio signals, and some algorithms are compared. Results will be extrapolated to the field of adaptive filtering on monophonic signals and the analysis of speech pathologies on futures works.