Analysis of derivative of instantaneous frequency and its application to voice activity detection

Abstract

Recently, the use of speech processing in a time–frequency domain that handles the phase spectrum in addition to the amplitude one has been increasing because many studies have revealed the importance of phase. Inspired by this motivation, this paper presents a new speech signal phase processing. The contributions of this paper include the following two points: a detailed analysis of a speech signal by considering a novel phase feature, a derivative of instantaneous frequency (DIF), and demonstrating a new phase-based voice activity detection (VAD) algorithm as one of the DIF’s applications. These contributions develop on our previous work that briefly introduced the DIF into VAD. In the analysis part, we investigate the DIF from the theoretical aspect and research the statistical distribution of the DIF of speech signals under various conditions. We also propose a new phase-based VAD algorithm via the statistical likelihood ratio, and use the DIF as an auxiliary feature to improve a conventional amplitude-based VAD method. The experimental results confirm the efficacy of the phase feature in the VAD application and the possibility of combining the phase and amplitude for better performance.