Analyzing Error Propagation in Korean Spoken QA with ASR-LLM Cascades
We analyze how automatic speech recognition (ASR) errors propagate through ASR--LLM cascades in Korean spoken question answering (SQA), focusing on downstream semantic failures that conventional ASR metrics cannot fully capture. Our analysis shows that the relative downstream degradation caused by ASR errors is consistent across LLMs with different absolute performance, suggesting that cascade degradation largely tracks ASR-stage information loss. We further identify single-character ASR errors as a particularly salient source of information loss in Korean, where even a minimal transcription difference can change the intended question and degrade downstream QA performance. Finally, an aux...
| Authors | Donghyuk Jung, Youngwon Choi |
|---|---|
| Primary category | cs.CL |
| Published | 17 May 2026 |
| Last updated at source | 18 August 2026 |
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