A per-layer gate predictor using speaker and acoustic-event embeddings dynamically prunes an OWSM speech model, cutting encoder GFLOPs by 56.7 while improving Europarl-ST BLEU by about 26% relative.
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Context-Driven Dynamic Pruning for Large Speech Foundation Models
A per-layer gate predictor using speaker and acoustic-event embeddings dynamically prunes an OWSM speech model, cutting encoder GFLOPs by 56.7 while improving Europarl-ST BLEU by about 26% relative.