Papers by Yongbeom Kim

1 papers
HiKE: Hierarchical Evaluation Framework for Korean-English Code-Switching Speech Recognition (2026.findings-eacl)

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Challenge: Recent advances in automatic speech recognition (ASR) have pushed error rates below 5% on standard monolingual benchmarks.
Approach: They propose a framework for the evaluation of multilingual ASR models using loanword labels and a hierarchical CS-level labeling scheme that allows for fine-tuning with synthetic CS data.
Outcome: The proposed framework provides a means for the precise evaluation of multilingual ASR models and fosters research in the field.

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