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Unsupervised Word Segmentation from Speech with Attention
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In: Interspeech 2018 ; https://hal.archives-ouvertes.fr/hal-01818092 ; Interspeech 2018, Sep 2018, Hyderabad, India (2018)
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Bayesian models for unit discovery on a very low resource language
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In: IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) ; https://hal.archives-ouvertes.fr/hal-01709589 ; IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Apr 2018, Calgary, Alberta, Canada (2018)
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Linguistic unit discovery from multi-modal inputs in unwritten languages: Summary of the “Speaking rosetta” JSALT 2017 workshop
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In: ICASSP 2018 - IEEE International Conference on Acoustics, Speech and Signal Processing ; https://hal.archives-ouvertes.fr/hal-01709578 ; ICASSP 2018 - IEEE International Conference on Acoustics, Speech and Signal Processing, Apr 2018, Calgary, Alberta, Canada (2018)
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Unsupervised Word Segmentation: does tone matter ?
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In: International Conference on Intelligent Text Processing and Computational Linguistics ; https://hal.archives-ouvertes.fr/hal-01910756 ; International Conference on Intelligent Text Processing and Computational Linguistics, Mar 2018, Hanoï, Vietnam (2018)
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Adaptor Grammars for the Linguist: Word Segmentation Experiments for Very Low-Resource Languages
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In: Workshop on Computational Research in Phonetics, Phonology, and Morphology ; https://hal.archives-ouvertes.fr/hal-01910757 ; Workshop on Computational Research in Phonetics, Phonology, and Morphology, Oct 2018, Bruxelles, Belgium. pp.32 - 42, ⟨10.18653/v1/P17⟩ (2018)
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Parallel Corpora in Mboshi (Bantu C25, Congo-Brazzaville)
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In: 11th edition of the Language Resources and Evaluation Conference (LREC 2018) ; https://hal.archives-ouvertes.fr/hal-01710043 ; 11th edition of the Language Resources and Evaluation Conference (LREC 2018), ELRA, May 2018, Miyazaki, Japan (2018)
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Linguistic unit discovery from multi-modal inputs in unwritten languages: Summary of the "Speaking Rosetta" JSALT 2017 Workshop ...
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Unsupervised Word Segmentation from Speech with Attention ...
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