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Speech tokenizers, despite being crucial for multimodal LLMs, primarily capture phonetic information, creating a semantic mismatch with text-derived semantics that hinders performance.
A new multimodal dataset links brain activity, muscle activation, and articulation in speech, opening doors to understanding the causal chain of speech production.
