Modality dropout training makes audio-visual target speaker extraction robust when audio or video is missing, across normalization layers and in causal configurations.
Model description The basic building block of MTSE system under test is the dual- path recurrent neural network (DPRNN) proposed in [20]
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Training Strategies for Modality Dropout Resilient Multi-Modal Target Speaker Extraction
Modality dropout training makes audio-visual target speaker extraction robust when audio or video is missing, across normalization layers and in causal configurations.