Phase-Processing For Voice Activity Detection: A Statistical Approach

TitlePhase-Processing For Voice Activity Detection: A Statistical Approach
Publication TypeConference Paper
Year of Publication2016
AuthorsStahl, J., Mowlaee P., & Kulmer J.
Conference Name 24th European Signal Processing Conference (EUSIPCO)
Pages1202-1206
Abstract

Conventional voice activity detectors (VAD) mostly rely on the magnitude of the complex valued DFT spectral coefficients. In this paper, the circular variance of the Discrete Fourier transform (DFT) coefficients is investigated in terms of its ability to represent speech activity in noise. To this end we model the circular variance as a random variable with different underlying distributions for the speech and the noise class. Based on this, we derive a binary hypothesis test relying only on the circular variance estimated from the noisy speech. The experimental results show a reasonable VAD performance justifying that amplitude-independent information can characterize speech in a convenient way.

 

URLhttps://ieeexplore.ieee.org/document/7760439/
Citation Key3404
Refereed DesignationRefereed
SPSC cross-references
Research Area: