Cross-Feature Knowledge Distillation Improves Speaker Verification with Discrete Audio Tokens

Jul 14, 2026

A new framework, Cross-Feature Knowledge Distillation (CFKD), enhances automatic speaker verification (ASV) by leveraging discrete audio tokens generated by neural audio codecs. CFKD works by training a codec-based student model to mimic the embedding space of a strong Fbank-based teacher model, resulting in significant improvements in ASV performance on VoxCeleb benchmarks. This approach enables discrete audio tokens to achieve accuracy levels close to those of traditional spectral features.

Why it matters: The work demonstrates that discrete audio tokens, which are efficient for compression, can be effectively used for speaker verification, potentially enabling more efficient and unified speech processing systems.

Full story at: arXiv Audio and Speech Processing ↗