Please use this identifier to cite or link to this item: doi:10.22028/D291-38636
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Title: Time-Aware Ancient Chinese Text Translation and Inference
Author(s): Chang, Ernie
Shiue, Yow-Ting
Yeh, Hui-Syuan
Demberg, Vera
Language: English
Publisher/Platform: arXiv
Year of Publication: 2021
DDC notations: 400 Language, linguistics
Publikation type: Other
Abstract: In this paper, we aim to address the challenges surrounding the translation of ancient Chinese text: (1) The linguistic gap due to the difference in eras results in translations that are poor in quality, and (2) most translations are missing the contextual information that is often very crucial to understanding the text. To this end, we improve upon past translation techniques by proposing the following: We reframe the task as a multi-label prediction task where the model predicts both the translation and its particular era. We observe that this helps to bridge the linguistic gap as chronological context is also used as auxiliary information. % As a natural step of generalization, we pivot on the modern Chinese translations to generate multilingual outputs. %We show experimentally the efficacy of our framework in producing quality translation outputs and also validate our framework on a collected task-specific parallel corpus. We validate our framework on a parallel corpus annotated with chronology information and show experimentally its efficacy in producing quality translation outputs. We release both the code and the data this https URL for future research.
URL of the first publication:
Link to this record: urn:nbn:de:bsz:291--ds-386366
Date of registration: 2-Jan-2023
Notes: Preprint
Faculty: MI - Fakultät für Mathematik und Informatik
Department: MI - Informatik
Professorship: MI - Prof. Dr. Vera Demberg
Collections:SciDok - Der Wissenschaftsserver der Universität des Saarlandes

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