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Findings of the LoResMT 2020 Shared Task on Zero-Shot for Low-Resource languages
This paper presents the findings of the LoResMT 2020 Shared Task on zero-shot translation for low resource languages.
Findings of the WMT 2023 Shared Task on Discourse-Level Literary Translation: A Fresh Orb in the Cosmos of LLMs
To foster progress in this domain, we hold a new shared task at WMT 2023, the first edition of the Discourse-Level Literary Translation.
Findings of the LoResMT 2021 Shared Task on COVID and Sign Language for Low-resource Languages
Maximum system performance was computed using BLEU and follow as 36. 0 for English--Irish, 34. 6 for Irish--English, 24. 2 for English--Marathi, and 31. 3 for Marathi--English.
Multiple Segmentations of Thai Sentences for Neural Machine Translation
Thai is a low-resource language, so it is often the case that data is not available in sufficient quantities to train an Neural Machine Translation (NMT) model which perform to a high level of quality.
The RGNLP Machine Translation Systems for WAT 2018
This paper presents the system description of Machine Translation (MT) system(s) for Indic Languages Multilingual Task for the 2018 edition of the WAT Shared Task.
Extracting In-domain Training Corpora for Neural Machine Translation Using Data Selection Methods
Data selection is a process used in selecting a subset of parallel data for the training of machine translation (MT) systems, so that 1) resources for training might be reduced, 2) trained models could perform better than those trained with the whole corpus, and/or 3) trained models are more tailored to specific domains.
Understanding Meanings in Multilingual Customer Feedback
Understanding and being able to react to customer feedback is the most fundamental task in providing good customer service.
Chinese-Portuguese Machine Translation: A Study on Building Parallel Corpora from Comparable Texts
The approach we used in this paper also shows a good example on how to boost performance of MT systems for low-resource language pairs.
IJCNLP-2017 Task 4: Customer Feedback Analysis
This document introduces the IJCNLP 2017 Shared Task on Customer Feedback Analysis.
Ethical Considerations in NLP Shared Tasks
Shared tasks are increasingly common in our field, and new challenges are suggested at almost every conference and workshop.
