Efficient harmonic peak detection of vowel sounds for enhanced voice activity detection. Issue 8 (1st October 2018)

• Record Type: Journal Article
• Authors: Kim, Jun Tae; Jung, Sung Hoon; Cho, Kwang‐Hyun
• Is Part Of: IET signal processing. Volume 12:Issue 8(2018)
• Page Start: 975
• Page End: 982
• Publication Date: 2018-10-01
• Subjects: signal classification -- speech recognition -- signal detection; spectral features -- robust VAD -- efficient harmonic peak location detection method -- signal‐to‐noise ratios -- vowel sounds -- enhanced voice activity detection -- speech segments -- background noise; Signal processing -- Periodicals; 621.3822
• DOI: 10.1049/iet-spr.2017.0553
• Languages: English
• ISSNs: 1751-9675

Abstract

Abstract : Voice activity detection (VAD) involves discriminating speech segments from background noise and is a critical step in numerous speech‐related applications. However, distinguishing speech from noise based on the properties of noise is fallible, because it is difficult to predict and characterise the noise occurring in real life. In this study, the authors instead focus on the intrinsic characteristics of speech. The harmonic peaks of vowel sounds have higher energies than the other spectral components of speech and are the speech features most likely to survive in most cases of severe noise. Therefore, the energy differences between harmonic peaks and other spectral features show promise for enabling robust VAD. To exploit this feature, the harmonic peaks must be accurately located. For this purpose, this study proposes an efficient harmonic peak location detection (HPD) method. Based on extensive experiments conducted in the presence of various noise types and signal‐to‐noise ratios, we found that VAD with the proposed HPD approach outperforms existing VAD methods and does so with reasonable computational cost and higher robustness.