StreamAlign: Streaming Text-Aligned Speech Tokenization
Text-aligned speech tokenization methods have emerged to better align speech tokens with LLM token spaces, enabling more effective utilization of pretrained LLMs. However, they rely on offline automatic speech recognition (ASR), leading to two key limitations: (i) the need for complete utterances before tokenization, precluding real-time streaming, and (ii) vocabulary mismatch between ASR and LLMs, which reduces acoustic granularity from the subword to the word level. We introduce StreamAlign, a text-aligned speech tokenization framework that enables streaming tokenization for real-time speech-text joint modeling. StreamAlign performs online speech-text alignment by combining character-le...
| Authors | Kang-wook Kim, Jinyoung Park, Jinsoo Kim et al. |
|---|---|
| Primary category | cs.CL |
| Published | 9 September 2026 |
| Last updated at source | 9 September 2026 |
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