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Universal Segmentations 1.0 (UniSegments 1.0)
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Žabokrtský, Zdeněk; Bafna, Nyati; Bodnár, Jan; Kyjánek, Lukáš; Svoboda, Emil; Ševčíková, Magda; Vidra, Jonáš; Angle, Sachi; Ansari, Ebrahim; Arkhangelskiy, Timofey; Batsuren, Khuyagbaatar; Bella, Gábor; Bertinetto, Pier Marco; Bonami, Olivier; Celata, Chiara; Daniel, Michael; Fedorenko, Alexei; Filko, Matea; Giunchiglia, Fausto; Haghdoost, Hamid; Hathout, Nabil; Khomchenkova, Irina; Khurshudyan, Victoria; Levonian, Dmitri; Litta, Eleonora; Medvedeva, Maria; Muralikrishna, S. N.; Namer, Fiammetta; Nikravesh, Mahshid; Padó, Sebastian; Passarotti, Marco; Plungian, Vladimir; Polyakov, Alexey; Potapov, Mihail; Pruthwik, Mishra; Rao B, Ashwath; Rubakov, Sergei; Samar, Husain; Sharma, Dipti Misra; Šnajder, Jan; Šojat, Krešimir; Štefanec, Vanja; Talamo, Luigi; Tribout, Delphine; Vodolazsky, Daniil; Vydrin, Arseniy; Zakirova, Aigul; Zeller, Britta. - : Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL), 2022
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Abstract:
Universal Segmentations (UniSegments) is a collection of lexical resources capturing morphological segmentations harmonised into a cross-linguistically consistent annotation scheme for many languages. The annotation scheme consists of simple tab-separated columns that stores a word and its morphological segmentations, including pieces of information about the word and the segmented units, e.g., part-of-speech categories, type of morphs/morphemes etc. The current public version of the collection contains 38 harmonised segmentation datasets covering 30 different languages.
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Keyword:
Armenian language; Bengali language; Catalan language; Croatian language; Czech language; English language; Erzya language; Finnish language; French language; German language; Hindi language; Hungarian language; Italian language; Kannada language; Komi-Zyrian language; Latin language; Malayalam language; Marathi language; Mari (Russia) language; Moksha language; Mongolian language; morph; morphemes; morphological dictionary; morphological segmentation; morphology; multilingual; Persian language; Polish language; Portuguese language; Russian language; segmentation; Serbo-Croatian language; Spanish language; Swedish language; Tajik language; Udmurt language; unisegments; universal segmentations; word segmentation
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URL: http://hdl.handle.net/11234/1-4629
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Investigating alignment interpretability for low-resource NMT
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In: ISSN: 0922-6567 ; EISSN: 1573-0573 ; Machine Translation ; https://hal.archives-ouvertes.fr/hal-03139744 ; Machine Translation, Springer Verlag, 2021, ⟨10.1007/s10590-020-09254-w⟩ (2021)
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Is there a bilingual disadvantage for word segmentation? A computational modeling approach
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In: ISSN: 0305-0009 ; EISSN: 1469-7602 ; Journal of Child Language ; https://hal.archives-ouvertes.fr/hal-03498905 ; Journal of Child Language, Cambridge University Press (CUP), 2021, pp.1-28. ⟨10.1017/S0305000921000568⟩ (2021)
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SM to: Is there a bilingual disadvantage for word segmentation? A computational modeling approach ...
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Early Tashelhiyt Berber word segmentation: the role of the Possible Word Constraint ...
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Discovering structure in speech recordings: Unsupervised learning of word and phoneme like units for automatic speech recognition
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In: Fraunhofer IAIS (2021)
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Handling cross and out-of-domain samples in Thai word segmentation
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In: 1003 ; 1016 (2021)
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Measuring (online) word segmentation in adults and children
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In: Dutch Journal of Applied Linguistics, Vol 10 (2021) (2021)
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Investigating Language Impact in Bilingual Approaches for Computational Language Documentation
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In: Proceedings of the 1st Joint SLTU and CCURL Workshop (SLTU-CCURL 2020), ; SLTU-CCURL workshop, LREC 2020 ; https://hal.archives-ouvertes.fr/hal-02895907 ; SLTU-CCURL workshop, LREC 2020, May 2020, Marseille, France (2020)
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F0 Slope and Mean: Cues to Speech Segmentation in French
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In: Interspeech 2020 ; https://hal.archives-ouvertes.fr/hal-03042331 ; Interspeech 2020, Oct 2020, Shanghai, China. pp.1610-1614, ⟨10.21437/Interspeech.2020-2509⟩ (2020)
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The learnability consequences of Zipfian distributions: Word Segmentation is Facilitated in More Predictable Distributions ...
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Data for: The learnability consequences of Zipfian distributions: Word Segmentation is Facilitated in More Predictable Distributions ...
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The learnability consequences of Zipfian distributions: Word Segmentation is Facilitated in More Predictable Distributions ...
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Automatic word count estimation from daylong child-centered recordings in various language environments using language-independent syllabification of speech
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Infants Segment Words from Songs—An EEG Study
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In: Brain Sciences ; Volume 10 ; Issue 1 (2020)
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Not all words are equally acquired: transitional probabilities and instructions affect the electrophysiological correlates of statistical learning
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Controlling Utterance Length in NMT-based Word Segmentation with Attention
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In: International Workshop on Spoken Language Translation ; https://hal.archives-ouvertes.fr/hal-02343206 ; International Workshop on Spoken Language Translation, Nov 2019, Hong-Kong, China (2019)
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Segmentability Differences Between Child-Directed and Adult-Directed Speech: A Systematic Test With an Ecologically Valid Corpus
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In: EISSN: 2470-2986 ; Open Mind ; https://hal.archives-ouvertes.fr/hal-02274050 ; Open Mind, MIT Press, 2019, 3, pp.13-22. ⟨10.1162/opmi_a_00022⟩ (2019)
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Unsupervised word discovery for computational language documentation ; Découverte non-supervisée de mots pour outiller la linguistique de terrain
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In: https://tel.archives-ouvertes.fr/tel-02286425 ; Artificial Intelligence [cs.AI]. Université Paris Saclay (COmUE), 2019. English. ⟨NNT : 2019SACLS062⟩ (2019)
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MiNgMatch—A Fast N-gram Model for Word Segmentation of the Ainu Language
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In: Information ; Volume 10 ; Issue 10 (2019)
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