Power spectral deviation-based voice activity detection incorporating teager energy for speech enhancement

Sang Kyun Kim, Sang Ick Kang, Young Jin Park, Sanghyuk Lee*, Sangmin Lee

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

6 Citations (Scopus)

Abstract

In this paper, we propose a robust voice activity detection (VAD) algorithm to effectively distinguish speech from non-speech in various noisy environments. The proposed VAD utilizes power spectral deviation (PSD), using Teager energy (TE) to provide a better representation of the PSD, resulting in improved decision performance for speech segments. In addition, the TE-based likelihood ratio and speech absence probability are derived in each frame to modify the PSD for further VAD.We evaluate the performance of the proposed VAD algorithm by objective testing in various environments and obtain better results that those attained by of the conventional methods.

Original languageEnglish
Article number58
JournalSymmetry
Volume8
Issue number7
DOIs
Publication statusPublished - 2016

Keywords

  • Power spectral deviation
  • Speech absence
  • Teager energy

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