KoALa-Bench: Evaluating Large Audio Language Models on Korean Speech Understanding and Faithfulness
Recent advances in large audio language models (LALMs) have enabled multilingual speech understanding. However, benchmarks for evaluating LALMs remain scarce for non-English languages, with Korean being one such underexplored case. In this paper, we introduce KoALa-Bench, a comprehensive benchmark for evaluating Korean speech understanding and speech faithfulness of LALMs. In particular, KoALa-Bench comprises six tasks. Four tasks evaluate fundamental speech understanding capabilities, including automatic speech recognition, speech translation, speech question answering, and speech instruction following, while the remaining two tasks evaluate speech faithfulness, motivated by our observat...
| Authors | Jinyoung Kim, Hyeongsoo Lim, Eunseo Seo et al. |
|---|---|
| Primary category | cs.CL |
| Published | 30 March 2026 |
| Last updated at source | 31 August 2026 |
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