Xiaomi-CocktailASR-1 Technical Report
Recently, large language model (LLM) based ASR models have achieved significant progress, yet they generally lack support for multi-speaker scenarios, where the cocktail party problem remains a critical bottleneck for further advancing ASR. Existing TS-ASR methods, including end-to-end architectures with speaker embeddings and latest LLM-based explorations suffer from degraded single-speaker performance and the inability to reject when the target speaker is absent. In this paper, we propose Xiaomi-CocktailASR-1, an LLM-based end-to-end TS-ASR architecture. By utilizing reference speech as voiceprint prompts, it directly transcribes the target speaker's speech without requiring speech sepa...
| Authors | Yiru Zhang, Hang Su, Lichun Fan et al. |
|---|---|
| Primary category | cs.SD |
| Published | 10 September 2026 |
| Last updated at source | 10 September 2026 |
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