Speech Endpoint Detection Using Gradient Based Edge Detection Techniques

This paper proposes a novel method for speech endpoint detection. The developed method utilises gradient based edge detection algorithms, used in image processing, to detect boundaries of continuous speech in noisy conditions. It is simple and has low computational complexity. The accuracy of the proposed method was evaluated and compared to the ITU-T G.729 Annex-B voice activity detection (VAD) algorithm. To do this, the two algorithms were tested using a synthetically produced noisy-speech database, consisting of noisy-speech signals at various lengths and SNR. The results indicated that the developed method outperforms the G.729-B VAD algorithm at various signal-to-noise ratios.