Llama-Mimi: Speech Language Models with Interleaved Semantic and Acoustic Tokens

• URL: http://arxiv.org/abs/2509.14882v1
• Date: Thu, 18 Sep 2025 12:00:07 GMT
• Title: Llama-Mimi: Speech Language Models with Interleaved Semantic and Acoustic Tokens
• Authors: Issa Sugiura, Shuhei Kurita, Yusuke Oda, Ryuichiro Higashinaka,
• Abstract summary: Llama-Mimi is a speech language model that uses a unified tokenizer and a single Transformer decoder.<n> Comprehensive evaluation shows that Llama-Mimi achieves state-of-the-art performance in acoustic consistency.
• Score: 14.66109161130445
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: We propose Llama-Mimi, a speech language model that uses a unified tokenizer and a single Transformer decoder to jointly model sequences of interleaved semantic and acoustic tokens. Comprehensive evaluation shows that Llama-Mimi achieves state-of-the-art performance in acoustic consistency and possesses the ability to preserve speaker identity. Our analysis further demonstrates that increasing the number of quantizers improves acoustic fidelity but degrades linguistic performance, highlighting the inherent challenge of maintaining long-term coherence. We additionally introduce an LLM-as-a-Judge-based evaluation to assess the spoken content quality of generated outputs. Our models, code, and speech samples are publicly available.

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