AI RESEARCH
DSA-Tokenizer: Disentangled Semantic-Acoustic Tokenization via Flow Matching-based Hierarchical Fusion
arXiv CS.AI
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ArXi:2601.09239v3 Announce Type: replace-cross Speech tokenizers are a key building block of fully discrete Speech LLMs. Existing tokenizers either prioritize semantic encoding, fuse semantic content with acoustic style inseparably, or achieve incomplete semantic-acoustic disentanglement. To achieve better disentanglement, we propose \textbf{DSA-Tokenizer}, which explicitly disentangles speech into discrete semantic and acoustic tokens via distinct optimization constraints.