Papers with LLM)-powered Automatic Speech Recognition
Language Family Matters: Evaluating SpeechLLMs Across Linguistic Boundaries (2026.eacl-short)
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| Challenge: | Existing approaches to integrate speech encoders with large language models (LLMs) have limited resources and lack linguistic relatedness. |
| Approach: | They propose a connector-sharing strategy based on linguistic family membership that allows one connector per family to share a frozen speech encoder with a pretrained LLM. |
| Outcome: | The proposed system reduces parameter count while improving generalization across domains, compared with existing connectors. |