Godard, P., Boito, M.Z., Ondel, L. et al. (4 more authors) (2018) Unsupervised word segmentation from speech with attention. In: Proceedings of Interspeech 2018. Interspeech 2018, 02-06 Sep 2018, Hyderabad, India. ISCA , pp. 2678-2682.
Abstract
We present a first attempt to perform attentional word segmentation directly from the speech signal, with the final goal to automatically identify lexical units in a low-resource, unwritten language (UL). Our methodology assumes a pairing between recordings in the UL with translations in a well-resourced language. It uses Acoustic Unit Discovery (AUD) to convert speech into a sequence of pseudo-phones that is segmented using neural soft-alignments produced by a neural machine translation model. Evaluation uses an actual Bantu UL, Mboshi; comparisons to monolingual and bilingual baselines illustrate the potential of attentional word segmentation for language documentation.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2018 ISCA. Reproduced in accordance with the publisher's self-archiving policy. |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 03 Sep 2019 15:00 |
Last Modified: | 03 Sep 2019 15:00 |
Status: | Published |
Publisher: | ISCA |
Refereed: | Yes |
Identification Number: | 10.21437/Interspeech.2018-1308 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:150390 |