A new article is available in IPOL: https://www.ipol.im/pub/art/2022/427/
Sam Perochon,
A Presentation and Short Discussion of rVAD-fast, a Fast Voice Activity
Detector,
Image Processing On Line, 12 (2022), pp. 404–419.
https://doi.org/10.5201/ipol.2022.427
Abstract
Voice activity detection (VAD) usually refers to the detection of human
voices in acoustic signals and is often used as a pre-processing step in
numerous audio signal processing tasks. The unsupervised method proposed
here was originally developed by Zheng-Hua Tan, Achintya kr. Sarkar and
Najim Dehak [Computer Speech & Language, 2020] and consists of a robust
segment-based approach. The voice activity detection stage follows two
denoising steps. The first one detects high energy segments using a
posteriori SNR weighted energy difference, and the second enhances the
speech using the MSNE-mod approach. Use cases or downstream tasks
include intrusion detection, speech-to-text, speaker diarization, or
emotion estimation.
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announces [email protected] - http://tools.ipol.im/mm/announce/
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