FLEURS-Kobani: Extending the FLEURS Dataset for Northern Kurdish

TL;DR

FLEURS-Kobani introduces a new Northern Kurdish speech dataset extending the FLEURS benchmark, enabling evaluation of ASR and speech translation for this under-resourced language.

Contribution

It provides the first public Northern Kurdish speech dataset and baseline models for ASR and speech translation tasks.

Findings

Achieved 28.11 WER in ASR with fine-tuned Whisper v3-large.

Attained 8.68 BLEU in speech translation from KMR to English.

Dataset includes 5,162 utterances recorded by 31 native speakers.

Abstract

FLEURS offers n-way parallel speech for 100+ languages, but Northern Kurdish is not one of them, which limits benchmarking for automatic speech recognition and speech translation tasks in this language. We present FLEURS-Kobani, a Northern Kurdish (ISO 639-3 KMR) spoken extension of the FLEURS benchmark. The FLEURS-Kobani dataset consists of 5,162 validated utterances, totaling 18 hours and 24 minutes. The data were recorded by 31 native speakers. It extends benchmark coverage to an under-resourced Kurdish variety. As baselines, we fine-tuned Whisper v3-large for ASR and E2E S2TT. A two-stage fine-tuning strategy (Common Voice to FLEURS-Kobani) yields the best ASR performance (WER 28.11, CER 9.84 on test). For E2E S2TT (KMR to EN), Whisper achieves 8.68 BLEU on test; we additionally report pivot-derived targets and a cascaded S2TT setup. FLEURS-Kobani provides the first public Northern Kurdish benchmark for evaluation of ASR, S2TT and S2ST tasks. The dataset is publicly released for research use under a CC BY 4.0 license.