Hoang Kiem

Also published as: Kiem Hoang


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BTL: a hybrid model for English-Vietnamese machine translation
Dinh Dien | Kiem Hoang | Eduard Hovy
Proceedings of Machine Translation Summit IX: Papers

Machine Translation (MT) is the most interesting and difficult task which has been posed since the beginning of computer history. The highest difficulty which computers had to face with, is the built-in ambiguity of Natural Languages. Formerly, a lot of human-devised rules have been used to disambiguate those ambiguities. Building such a complete rule-set is time-consuming and labor-intensive task whilst it doesn’t cover all the cases. Besides, when the scale of system increases, it is very difficult to control that rule-set. In this paper, we present a new model of learning-based MT (entitled BTL: Bitext-Transfer Learning) that learns from bilingual corpus to extract disambiguating rules. This model has been experimented in English-to-Vietnamese MT system (EVT) and it gave encouraging results.

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POS-Tagger for English-Vietnamese Bilingual Corpus
Dinh Dien | Hoang Kiem
Proceedings of the HLT-NAACL 2003 Workshop on Building and Using Parallel Texts: Data Driven Machine Translation and Beyond

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Towards a Multi-Objective Corpus for Vietnamese Language
Hai Quan Vu | Nam Trung Pham | Duc Hoang Ha Nguyen | Bao Toan Huynh | Hoai Bac Le | Kiem Hoang
Proceedings of the 17th Pacific Asia Conference on Language, Information and Computation


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An Approach to Parsing Vietnamese Noun Compounds
Dinh Dien | Hoang Kiem
Proceedings of the Seventh International Workshop on Parsing Technologies