A lightweight VAD model with a learnable sinc filterbank and a squared-margin ranking loss reports higher AUROC and F2 scores on AVA-Speech and ACAM using only 8.0k parameters.
Real-time causal spectro-temporal voice activity detection based on convolutional encoding and residual decoding,
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SincQDR-VAD: A Noise-Robust Voice Activity Detection Framework Leveraging Learnable Filters and Ranking-Aware Optimization
A lightweight VAD model with a learnable sinc filterbank and a squared-margin ranking loss reports higher AUROC and F2 scores on AVA-Speech and ACAM using only 8.0k parameters.