Comparison of Self-Supervised Speech Pre-Training Methods on Flemish Dutch ...
Recent research in speech processing exhibits a growing interest in unsupervised and self-supervised representation learning from unlabelled data to alleviate the need for large amounts of annotated data. We investigate several popular pre-training methods and apply them to Flemish Dutch. We compare off-the-shelf English pre-trained models to models trained on an increasing amount of Flemish data. We find that the most important factors for positive transfer to downstream speech recognition tasks include a substantial amount of data and a matching pre-training domain. Ideally, we also finetune... Mehr ...
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Dokumenttyp: | Artikel |
Erscheinungsdatum: | 2021 |
Verlag/Hrsg.: |
arXiv
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Schlagwörter: | Audio and Speech Processing eess.AS / Sound cs.SD / FOS: Electrical engineering / electronic engineering / information engineering / FOS: Computer and information sciences |
Sprache: | unknown |
Permalink: | https://search.fid-benelux.de/Record/base-29060021 |
Datenquelle: | BASE; Originalkatalog |
Powered By: | BASE |
Link(s) : | https://dx.doi.org/10.48550/arxiv.2109.14357 |