Papers with acquisition process

4 papers
Analysis on Unsupervised Acquisition Process of Bilingual Vocabulary through Iterative Back-Translation (2024.lrec-main)

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Challenge: Existing studies have demonstrated the effectiveness of iterative back-translation, but its reason has not been sufficiently elucidated.
Approach: They propose a method for machine translation known as iterative back-translation . they use two monolingual data to create a pseudo-bilingual data and update translation models .
Outcome: The proposed method improves translation quality and improves BLEU.
Cross-Cultural Transfer Learning for Text Classification (D19-1)

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Challenge: a large dataset is required to achieve competitive performance in most natural language tasks. large datasets are expensive, time consuming, and error-prone.
Approach: They propose a transfer-learning framework that leverages bilingual corpora for natural language text classification using no task-specific data.
Outcome: The proposed framework can achieve good performance on formality classification and sarcasm detection tasks without any task-specific labeled data.
DGS-Fabeln-1: A Multi-Angle Parallel Corpus of Fairy Tales between German Sign Language and German Text (2024.lrec-main)

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Challenge: a parallel corpus of German text and videos containing fairy tales interpreted into the German Sign Language (DGS) is the first corpus filmed from 7 angles and one of the few sign language corpora globally which have been filmed simultaneously.
Approach: They present a parallel corpus of German fairy tales interpreted by a native DGS signer.
Outcome: The proposed corpus is the first semi-naturally expressed DGS that has been filmed from 7 angles and where the listener has been simultaneously filmed.
Empowering Oneida Language Revitalization: Development of an Oneida Verb Conjugator (2024.lrec-main)

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Challenge: Oneida is a polysynthetic North American Indigenous language . currently, there are only 45 native speakers in Canada and 102 worldwide .
Approach: They propose to use the Gramble framework to develop a digital Oneida verb conjugator that can demonstrate its users the correct conjugations of verbs and let learners generate practice materials tailored to their unique learning trajectories.
Outcome: The proposed system can demonstrate its users the correct conjugations of verbs and can also let learners generate practice materials tailored to their unique learning trajectories.

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