Eng Siong Chng


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Adapting BERT for Word Sense Disambiguation with Gloss Selection Objective and Example Sentences
Boon Peng Yap | Andrew Koh | Eng Siong Chng
Findings of the Association for Computational Linguistics: EMNLP 2020

Domain adaptation or transfer learning using pre-trained language models such as BERT has proven to be an effective approach for many natural language processing tasks. In this work, we propose to formulate word sense disambiguation as a relevance ranking task, and fine-tune BERT on sequence-pair ranking task to select the most probable sense definition given a context sentence and a list of candidate sense definitions. We also introduce a data augmentation technique for WSD using existing example sentences from WordNet. Using the proposed training objective and data augmentation technique, our models are able to achieve state-of-the-art results on the English all-words benchmark datasets.


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Named-Entity Tagging and Domain adaptation for Better Customized Translation
Zhongwei Li | Xuancong Wang | Ai Ti Aw | Eng Siong Chng | Haizhou Li
Proceedings of the Seventh Named Entities Workshop

Customized translation need pay spe-cial attention to the target domain ter-minology especially the named-entities for the domain. Adding linguistic features to neural machine translation (NMT) has been shown to benefit translation in many studies. In this paper, we further demonstrate that adding named-entity (NE) feature with named-entity recognition (NER) into the source language produces better translation with NMT. Our experiments show that by just including the different NE classes and boundary tags, we can increase the BLEU score by around 1 to 2 points using the standard test sets from WMT2017. We also show that adding NE tags using NER and applying in-domain adaptation can be combined to further improve customized machine translation.


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Modeling of term-distance and term-occurrence information for improving n-gram language model performance
Tze Yuang Chong | Rafael E. Banchs | Eng Siong Chng | Haizhou Li
Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)


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An Empirical Evaluation of Stop Word Removal in Statistical Machine Translation
Tze Yuang Chong | Rafael Banchs | Eng Siong Chng
Proceedings of the Joint Workshop on Exploiting Synergies between Information Retrieval and Machine Translation (ESIRMT) and Hybrid Approaches to Machine Translation (HyTra)


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Non-Isomorphic Forest Pair Translation
Hui Zhang | Min Zhang | Haizhou Li | Eng Siong Chng
Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing