2 papers
cs.CL2025
Iterative refinement, not training objective, makes HuBERT behave differently from wav2vec 2.0
Robin Huo, Ewan Dunbar
Self-supervised models for speech representation learning now see widespread use for their versatility and performance on downstream tasks, but the effect of model architecture on…
cs.CL2025
The Faetar Benchmark: Speech Recognition in a Very Under-Resourced Language
Michael Ong, Sean Robertson, Leo Peckham +7
We introduce the Faetar Automatic Speech Recognition Benchmark, a benchmark corpus designed to push the limits of current approaches to low-resource speech recognition. Faetar, a F…