BlasBench: An Open Benchmark for Irish Speech Recognition

April 12, 2026 ยท Grace Period ยท + Add venue

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Authors Jyoutir Raj, John Conway arXiv ID 2604.10736 Category cs.CL: Computation & Language Cross-listed cs.SD Citations 0
Abstract
No open Irish-specific benchmark compares end-user ASR systems under a shared Irish-aware evaluation protocol. To solve this, we release BlasBench, an open evaluation harness with Irish-aware text normalisation that preserves fadas, lenition, and eclipsis. We benchmark 12 systems across four architecture families on Common Voice ga-IE and FLEURS ga-IE. All Whisper variants exceed 100% WER. The best open model (omniASR LLM 7B) achieves 30.65% WER on Common Voice and 39.09% on FLEURS. We noticed models fine-tuned on Common Voice lose 33-43 WER points on FLEURS, revealing a generalisation gap that is invisible to single-dataset evaluation.
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