Jan Cernocky

HYBRID PRUNING: IN-SITU COMPRESSION OF SELF-SUPERVISED SPEECH MODELS FOR SPEAKER VERIFICATION AND ANTI-SPOOFING

Although large-scale self-supervised learning (SSL) models like WavLM have achieved state-of-the-art performance in speech processing, their significant size impedes deployment on resource-constrained devices. While structured pruning is a key technique for model compression, existing methods typica…