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Unsupervised Word Segmentation from Discrete Speech Units in Low-Resource Settings. (arXiv:2106.04298v2 [cs.CL] UPDATED)
May 19, 2022, 1:11 a.m. | Marcely Zanon Boito, Bolaji Yusuf, Lucas Ondel, Aline Villavicencio, Laurent Besacier
cs.CL updates on arXiv.org arxiv.org
Documenting languages helps to prevent the extinction of endangered dialects,
many of which are otherwise expected to disappear by the end of the century.
When documenting oral languages, unsupervised word segmentation (UWS) from
speech is a useful, yet challenging, task. It consists in producing time-stamps
for slicing utterances into smaller segments corresponding to words, being
performed from phonetic transcriptions, or in the absence of these, from the
output of unsupervised speech discretization models. These discretization
models are trained using raw …
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