FusionVAD shows that simple addition or concatenation of MFCC and pre-trained model features outperforms cross-attention fusion for voice activity detection, with the best model beating Pyannote by 2.04 average DER.
MFCC vs PTM Features Pre-trained model based features have proven effective for various speech tasks, including V AD
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Attention Is Not Always the Answer: Optimizing Voice Activity Detection with Simple Feature Fusion
FusionVAD shows that simple addition or concatenation of MFCC and pre-trained model features outperforms cross-attention fusion for voice activity detection, with the best model beating Pyannote by 2.04 average DER.