CHALIS: A Challenge Dataset for Language Identification in Difficult Scenarios
We present CHALIS (Challenging Language Identification Samples), a new benchmark dataset explicitly designed to address difficult cases in language identification: cousin languages and orthographic noise. Our dataset has two parts: First, we collected sentences shared across mutually intelligible language pairs (Czech/Slovak, Spanish/Catalan, Portuguese/Galician, Danish/Norwegian). The second part tests for orthography noise: we transliterate text across multiple scripts, remove diacritics, simulate homoglyph attacks, and use Internet slang. We evaluate four widely used language identification systems on CHALIS and demonstrate that all struggle substantially in these scenarios, especially...
| Authors | Michal Tichý, Jindřich Libovický |
|---|---|
| Primary category | cs.CL |
| Published | 4 June 2026 |
| Last updated at source | 4 June 2026 |
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