thetaone-ai/HiKE
HiKE: Hierarchical Evaluation Framework for Korean-English Code-Switching Speech Recognition Gio Paik*, Yongbeom Kim, Soungmin Lee, Sangmin Ahn†, and Chanwoo Kim†, EACL Findings 2026* Corresponding Author, † Equal Contribution ✨ Code | 🤗 Dataset | 📖 Paper Introduction HiKE is the first Korean-English Code-Switching (CS) Automatic Speech Recognition (ASR) benchmark composed of high-quality, natural CS data across various topics. We use Mixed Error Rate (MER)… See the full description on the dataset page: https://huggingface.co/datasets/thetaone-ai/HiKE.
| Author / organization | thetaone-ai |
|---|---|
| License (as declared) | apache-2.0 |
| Downloads | 216 (as reported by Hugging Face) |
| Likes | 4 |
| Created | 1 October 2025 |
| Last updated at source | 13 April 2026 |
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- 17 Oct 2026 Description: HiKE: Hierarchical Evaluation Framework for Korean-English Code-Switching Speech Recognition Gio Paik*, Yongbeom Kim, Soungmin Lee, Sangmin Ahn†, and Chanwoo Kim†, EACL Findings 2026* Corresponding Author, † Equal Contribution ✨ Code | 🤗 D → HiKE: Hierarchical Evaluation Framework for Korean-English Code-Switching Speech Recognition Gio Paik*, Yongbeom Kim, Soungmin Lee, Sangmin Ahn†, and Chanwoo Kim†, EACL Findings 2026* Corresponding Author, † Equal Contribution ✨ Code | 🤗 D
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