A Free/Open-Source Morphological Analyser and Generator for Sakha

Sardana Ivanova; Jonathan Washington; Francis M. Tyers

A Free/Open-Source Morphological Analyser and Generator for Sakha

Sardana Ivanova, Jonathan Washington, Francis M. Tyers

Avdelningen för datavetenskap

Forskningsoutput: Kapitel i bok/rapport/konferenshandling › Konferensbidrag › Vetenskaplig › Peer review

Sammanfattning

We present, to our knowledge, the first ever published morphological analyser and generator for Sakha, a marginalised language of Siberia. The transducer, developed using HFST, has coverage of solidly above 90%, and high precision. In the development of the analyser, we have expanded linguistic knowledge about Sakha, and developed strategies for complex grammatical patterns. The transducer is already being used in downstream tasks, including computer assisted language learning applications for linguistic maintenance and computational linguistic shared tasks.

Originalspråk	engelska
Titel på värdpublikation	LREC 2022, THIRTEEN INTERNATIONAL CONFERENCE ON LANGUAGE RESOURCES AND EVALUATION : LREC 2022 Conference Proceedings
Antal sidor	6
Förlag	European Languages Resources Association (ELRA)
Utgivningsdatum	juni 2022
Sidor	5137-5142
ISBN (elektroniskt)	979-10-95546-72-6
Status	Publicerad - juni 2022
MoE-publikationstyp	A4 Artikel i en konferenspublikation
Evenemang	Language Resources and Evaluation Conference - Marseille, Frankrike Varaktighet: 21 juni 2022 → 23 juni 2022 Konferensnummer: 13 https://lrec2022.lrec-conf.org/en/

Vetenskapsgrenar

113 Data- och informationsvetenskap

Åtkomst av dokument

2022.lrec-1.550Slutlig publicerad version, 3,29 MBLicens: CC BY-NC

http://www.lrec-conf.org/proceedings/lrec2022/pdf/2022.lrec-1.550.pdfLicens: CC BY-NC

Citera det här

Ivanova, S., Washington, J., & Tyers, F. M. (2022). A Free/Open-Source Morphological Analyser and Generator for Sakha. I LREC 2022, THIRTEEN INTERNATIONAL CONFERENCE ON LANGUAGE RESOURCES AND EVALUATION: LREC 2022 Conference Proceedings (s. 5137-5142). European Languages Resources Association (ELRA) . http://www.lrec-conf.org/proceedings/lrec2022/pdf/2022.lrec-1.550.pdf

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abstract = "We present, to our knowledge, the first ever published morphological analyser and generator for Sakha, a marginalised language of Siberia. The transducer, developed using HFST, has coverage of solidly above 90%, and high precision. In the development of the analyser, we have expanded linguistic knowledge about Sakha, and developed strategies for complex grammatical patterns. The transducer is already being used in downstream tasks, including computer assisted language learning applications for linguistic maintenance and computational linguistic shared tasks.",

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author = "Sardana Ivanova and Jonathan Washington and Tyers, {Francis M.}",

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Ivanova, S, Washington, J & Tyers, FM 2022, A Free/Open-Source Morphological Analyser and Generator for Sakha. i LREC 2022, THIRTEEN INTERNATIONAL CONFERENCE ON LANGUAGE RESOURCES AND EVALUATION: LREC 2022 Conference Proceedings. European Languages Resources Association (ELRA) , s. 5137-5142, Language Resources and Evaluation Conference, Marseille, Frankrike, 21/06/2022. <http://www.lrec-conf.org/proceedings/lrec2022/pdf/2022.lrec-1.550.pdf>

A Free/Open-Source Morphological Analyser and Generator for Sakha. / Ivanova, Sardana; Washington, Jonathan; Tyers, Francis M.
LREC 2022, THIRTEEN INTERNATIONAL CONFERENCE ON LANGUAGE RESOURCES AND EVALUATION: LREC 2022 Conference Proceedings. European Languages Resources Association (ELRA) , 2022. s. 5137-5142.

Forskningsoutput: Kapitel i bok/rapport/konferenshandling › Konferensbidrag › Vetenskaplig › Peer review

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N2 - We present, to our knowledge, the first ever published morphological analyser and generator for Sakha, a marginalised language of Siberia. The transducer, developed using HFST, has coverage of solidly above 90%, and high precision. In the development of the analyser, we have expanded linguistic knowledge about Sakha, and developed strategies for complex grammatical patterns. The transducer is already being used in downstream tasks, including computer assisted language learning applications for linguistic maintenance and computational linguistic shared tasks.

AB - We present, to our knowledge, the first ever published morphological analyser and generator for Sakha, a marginalised language of Siberia. The transducer, developed using HFST, has coverage of solidly above 90%, and high precision. In the development of the analyser, we have expanded linguistic knowledge about Sakha, and developed strategies for complex grammatical patterns. The transducer is already being used in downstream tasks, including computer assisted language learning applications for linguistic maintenance and computational linguistic shared tasks.

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