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Glottal Stops in Upper Sorbian: A Data-Driven Approach
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In: Fraunhofer IKTS (2021)
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| 2 |
Automatic phonetic classification of vocalic allophones in Tol
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In: Proceedings of the Linguistic Society of America; Vol 6, No 1 (2021): Proceedings of the Linguistic Society of America; 403–410 ; 2473-8689 (2021)
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Spoken word corpus and dictionary definition for an African language
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In: EISSN: 2416-5999 ; Journal of Data Mining and Digital Humanities ; https://hal.archives-ouvertes.fr/hal-02912202 ; Journal of Data Mining and Digital Humanities, Episciences.org, 2020, Special Issue on Collecting, Preserving, and Disseminating Endangered Cultural Heritage for New Understandings through Multilingual Approaches (2020)
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Leveraging orthographic information to improve machine translation of under-resourced languages
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| 5 |
Cardamom: Comparative deep models for minority and historical languages
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| 6 |
Preserving Endangered European Cultural Heritage and Languages Through Translated Literary Texts
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In: First International ConferenceLanguage Technologies for All (LT4All): Enabling Language Diversity & Multilingualism Worldwide ; https://hal.archives-ouvertes.fr/hal-03086002 ; First International ConferenceLanguage Technologies for All (LT4All): Enabling Language Diversity & Multilingualism Worldwide, Dec 2019, Paris, France (2019)
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| 7 |
A Sustainable and Open Access Knowledge Organization Model to Preserve Cultural Heritage and Language Diversity
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In: ISSN: 2078-2489 ; Information ; https://hal.archives-ouvertes.fr/hal-02565134 ; Information, MDPI, 2019, 10 (10), pp.303. ⟨10.3390/info10100303⟩ (2019)
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| 8 |
Translation-Based Dictionary Alignment for Under-Resourced Bantu Languages
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Eckart, Thomas; Bosch, Sonja; Goldhahn, Dirk. - : Schloss Dagstuhl - Leibniz-Zentrum fuer Informatik, 2019. : OASIcs - OpenAccess Series in Informatics. 2nd Conference on Language, Data and Knowledge (LDK 2019), 2019
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| 9 |
Comparison of Different Orthographies for Machine Translation of Under-Resourced Dravidian Languages
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Abstract:
Under-resourced languages are a significant challenge for statistical approaches to machine translation, and recently it has been shown that the usage of training data from closely-related languages can improve machine translation quality of these languages. While languages within the same language family share many properties, many under-resourced languages are written in their own native script, which makes taking advantage of these language similarities difficult. In this paper, we propose to alleviate the problem of different scripts by transcribing the native script into common representation i.e. the Latin script or the International Phonetic Alphabet (IPA). In particular, we compare the difference between coarse-grained transliteration to the Latin script and fine-grained IPA transliteration. We performed experiments on the language pairs English-Tamil, English-Telugu, and English-Kannada translation task. Our results show improvements in terms of the BLEU, METEOR and chrF scores from transliteration and we find that the transliteration into the Latin script outperforms the fine-grained IPA transcription.
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Keyword:
Data processing Computer science; Dravidian languages; International Phonetic Alphabet; IPA; M; Machine translation; Phonetic transcription; Transliteration; Under-resourced languages
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URN:
urn:nbn:de:0030-drops-103700
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URL: https://drops.dagstuhl.de/opus/volltexte/2019/10370/
https://doi.org/10.4230/OASIcs.LDK.2019.6
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| 11 |
WordNet gloss translation for under-resourced languages using multilingual neural machine translation
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| 12 |
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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| 13 |
A Sustainable and Open Access Knowledge Organization Model to Preserve Cultural Heritage and Language Diversity
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In: Information ; Volume 10 ; Issue 10 (2019)
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| 17 |
Crowdsourcing Model for Multilingual Corpus and Knowledge Construction: The Case of Transnational Mark Twain
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In: ISSN: 0324-8194 ; ZIN. Issues in Information Science. Information Studies ; https://hal.archives-ouvertes.fr/hal-01868242 ; ZIN. Issues in Information Science. Information Studies, 2018, 56 (1), pp.21-32 ; http://www.sbp.pl/en/article/?cid=3449&prev=467 (2018)
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