FLEURS-Kobani: Extending FLEURS dataset for Northern Kurdish
Proceedings of the First Workshop on Dialects in NLP — A Resource Perspective
Abstract
We present FLEURS-Kobani, a Northern Kurdish (ISO 639-3 KMR) spoken extension of FLEURS benchmark. Although FLEURS offers n-way parallel speech for 100+ languages, Northern Kurdish is absent, limits benchmarking automatic speech recognition and speech translation tasks for this language. The FLEURS-Kobani dataset consists of 5,162 validated utterances, totaling 18 hours and 24 minutes. As baselines, we fine-tuned Whisper v3-large for ASR and E2E S2TT. A two-stage fine-tuning strategy (Common Voice→FLEURS-Kobani) yields the best ASR performance (WER 28.11, CER 9.84 on test). For end-to-end S2TT (KMR→EN), Whisper achieves 8.68 BLEU on test; we additionally report pivot-derived targets and a cascaded S2TT setup. FLEURS-Kobani provides the first Northern Kurdish public benchmark for evaluation of ASR, S2TT and S2ST tasks. The data can be accessed (LINK IS BLANK DUE TO REVISION RULES) under CC BY 4.0 license.