An overview of speech endpoint detection algorithms. (March 2020)

• Record Type: Journal Article
• Authors: Zhang, Tao; Shao, Yangyang; Wu, Yaqin; Geng, Yanzhang; Fan, Long
• Is Part Of: Applied acoustics. Volume 160(2020)
• Publication Date: 2020-03
• Subjects: Speech endpoint detection -- Time domain -- Frequency domain -- Cepstrum domain -- Neural network; Acoustical engineering -- Periodicals; Periodicals; 620.2
• DOI: 10.1016/j.apacoust.2019.107133
• Languages: English
• ISSNs: 0003-682X

Abstract

Abstract: Speech endpoint detection is an important part of modern speech information processing technology. The success of endpoint detection directly improves the performance and quality of speech coding, speech recognition, speech synthesis and human interaction. The robustness and detection accuracy of algorithms have always been hot topics for many scholars in the condition of low Signal-to-Noise Ratio (SNR) and complex noise. In this paper, we aim to provide an overview of the state-of-the-art in time domain, frequency domain and cepstrum domain for speech endpoint detection algorithms and to cast a glance at the challenges for future research.