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1
Unsupervised word segmentation from speech with attention
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.
URL: http://eprints.whiterose.ac.uk/150390/
http://eprints.whiterose.ac.uk/150390/7/1308.pdf
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2
Similarity Measures for the Detection of Clinical Conditions with Verbal Fluency Tasks
Paula, F.; Wilkens, R.; Idiart, M.. - : Association for Computational Linguistics, 2018
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3
A corpus study of verbal multiword expressions in Brazilian Portuguese
Ramisch, C.; Ramisch, R.; Zilio, L.. - : Springer International Publishing, 2018
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4
Unwritten languages demand attention too! Word discovery with encoder-decoder models
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5
Restricted recurrent neural tensor networks: Exploiting word frequency and compositionality
Salle, A.; Villavicencio, A.. - : Association for Computational Linguistics, 2018
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