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arXiv · 2508.11771

Investigating Transcription Normalization in the Faetar ASR Benchmark

Leo Peckham·Michael Ong·Naomi Nagy·Ewan Dunbar
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Abstract

We examine the role of transcription inconsistencies in the Faetar Automatic Speech Recognition benchmark, a challenging low-resource ASR benchmark. With the help of a small, hand-constructed lexicon, we conclude that find that, while inconsistencies do exist in the transcriptions, they are not the main challenge in the task. We also demonstrate that bigram word-based language modelling is of no added benefit, but that constraining decoding to a finite lexicon can be beneficial. The task remains extremely difficult.

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Leo Peckham, Michael Ong, Naomi Nagy, Ewan Dunbar. 2025-08-15. Investigating Transcription Normalization in the Faetar ASR Benchmark. https://arxiv.org/abs/2508.11771

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