Language Family Matters: Evaluating LLM-Based ASR Across Linguistic Boundaries

Excerpt

arXiv:2601.18899v3 Announce Type: replace Abstract: Large Language Model (LLM)-powered Automatic Speech Recognition (ASR) systems achieve strong performance with limited resources by linking a frozen speech encoder to a pretrained LLM via a lightweight connector. Prior work trains a separate connector per language, overlooking linguistic relatedness. We propose an efficient and novel connector-sharing strategy based on linguistic family membership, enabling one connector per family, and empirica