Priming Ancient Korean Neural Machine Translation

Chanjun Park; Seolhwa Lee; Jaehyung Seo; Hyeonseok Moon; Sugyeong Eo; Heuiseok Lim

Priming Ancient Korean Neural Machine Translation

Chanjun Park, Seolhwa Lee, Jaehyung Seo, Hyeonseok Moon, Sugyeong Eo, Heuiseok Lim

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

In recent years, there has been an increasing need for the restoration and translation of historical languages. In this study, we attempt to translate historical records in ancient Korean language based on neural machine translation (NMT). Inspired by priming, a cognitive science theory that two different stimuli influence each other, we propose novel priming ancient-Korean NMT (AKNMT) using bilingual subword embedding initialization with structural property awareness in the ancient documents. Finally, we obtain state-of-the-art results in the AKNMT task. To the best of our knowledge, we confirm the possibility of developing a human-centric model that incorporates the concepts of cognitive science and analyzes the result from the perspective of interference and cognitive dissonance theory for the first time.

Original language	English
Title of host publication	2022 Language Resources and Evaluation Conference, LREC 2022
Editors	Nicoletta Calzolari, Frederic Bechet, Philippe Blache, Khalid Choukri, Christopher Cieri, Thierry Declerck, Sara Goggi, Hitoshi Isahara, Bente Maegaard, Joseph Mariani, Helene Mazo, Jan Odijk, Stelios Piperidis
Publisher	European Language Resources Association (ELRA)
Pages	22-28
Number of pages	7
ISBN (Electronic)	9791095546726
Publication status	Published - 2022
Event	13th International Conference on Language Resources and Evaluation Conference, LREC 2022 - Marseille, France Duration: 2022 Jun 20 → 2022 Jun 25

Publication series

Name	2022 Language Resources and Evaluation Conference, LREC 2022

Conference

Conference	13th International Conference on Language Resources and Evaluation Conference, LREC 2022
Country/Territory	France
City	Marseille
Period	22/6/20 → 22/6/25

Bibliographical note

Funding Information:
This research was supported by the MSIT(Ministry of Science and ICT), Korea, under the ITRC(Information Technology Research Center) support program(IITP-2018-0-01405) supervised by the IITP(Institute for Information & Communications Technology Planning & Evaluation) and supported by Institute of Information & communications Technology Planning & Evaluation(IITP) grant funded by the Korea government(MSIT) (No. 2020-0-00368, A Neural-Symbolic Model for Knowledge Acquisition and Inference Techniques).

Publisher Copyright:
© European Language Resources Association (ELRA), licensed under CC-BY-NC-4.0.

Keywords

Ancient-Korean Neural Machine Translation
Neural Machine Translation
Priming

ASJC Scopus subject areas

Language and Linguistics
Library and Information Sciences
Linguistics and Language
Education

Cite this

Park, C., Lee, S., Seo, J., Moon, H., Eo, S., & Lim, H. (2022). Priming Ancient Korean Neural Machine Translation. In N. Calzolari, F. Bechet, P. Blache, K. Choukri, C. Cieri, T. Declerck, S. Goggi, H. Isahara, B. Maegaard, J. Mariani, H. Mazo, J. Odijk, & S. Piperidis (Eds.), 2022 Language Resources and Evaluation Conference, LREC 2022 (pp. 22-28). (2022 Language Resources and Evaluation Conference, LREC 2022). European Language Resources Association (ELRA).

Priming Ancient Korean Neural Machine Translation. / Park, Chanjun; Lee, Seolhwa; Seo, Jaehyung et al.
2022 Language Resources and Evaluation Conference, LREC 2022. ed. / Nicoletta Calzolari; Frederic Bechet; Philippe Blache; Khalid Choukri; Christopher Cieri; Thierry Declerck; Sara Goggi; Hitoshi Isahara; Bente Maegaard; Joseph Mariani; Helene Mazo; Jan Odijk; Stelios Piperidis. European Language Resources Association (ELRA), 2022. p. 22-28 (2022 Language Resources and Evaluation Conference, LREC 2022).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Park, C, Lee, S, Seo, J, Moon, H, Eo, S & Lim, H 2022, Priming Ancient Korean Neural Machine Translation. in N Calzolari, F Bechet, P Blache, K Choukri, C Cieri, T Declerck, S Goggi, H Isahara, B Maegaard, J Mariani, H Mazo, J Odijk & S Piperidis (eds), 2022 Language Resources and Evaluation Conference, LREC 2022. 2022 Language Resources and Evaluation Conference, LREC 2022, European Language Resources Association (ELRA), pp. 22-28, 13th International Conference on Language Resources and Evaluation Conference, LREC 2022, Marseille, France, 22/6/20.

Park C, Lee S, Seo J, Moon H, Eo S, Lim H. Priming Ancient Korean Neural Machine Translation. In Calzolari N, Bechet F, Blache P, Choukri K, Cieri C, Declerck T, Goggi S, Isahara H, Maegaard B, Mariani J, Mazo H, Odijk J, Piperidis S, editors, 2022 Language Resources and Evaluation Conference, LREC 2022. European Language Resources Association (ELRA). 2022. p. 22-28. (2022 Language Resources and Evaluation Conference, LREC 2022).

Park, Chanjun ; Lee, Seolhwa ; Seo, Jaehyung et al. / Priming Ancient Korean Neural Machine Translation. 2022 Language Resources and Evaluation Conference, LREC 2022. editor / Nicoletta Calzolari ; Frederic Bechet ; Philippe Blache ; Khalid Choukri ; Christopher Cieri ; Thierry Declerck ; Sara Goggi ; Hitoshi Isahara ; Bente Maegaard ; Joseph Mariani ; Helene Mazo ; Jan Odijk ; Stelios Piperidis. European Language Resources Association (ELRA), 2022. pp. 22-28 (2022 Language Resources and Evaluation Conference, LREC 2022).

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Priming Ancient Korean Neural Machine Translation

Abstract

Publication series

Conference

Bibliographical note

Keywords

ASJC Scopus subject areas

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Cite this