This paper presents an empirical study on the application of the maximum entropy approach for part-of-speech tagging of Vietnamese text, a language with special characteristics which largely distinguish it from occidental languages. Our best tagger explores and includes useful knowledge sources for tagging Vietnamese text and gives a 93.40%overall accuracy and a 80.69%unknown word accuracy on a test set of the Vietnamese treebank. Our tagger significantly outperforms the tagger that is being used for building the Vietnamese treebank, and as far as we are aware, this is the best tagging result ever published for the Vietnamese language.

We present in this paper a comparison between three segmentation systems for the Vietnamese language. Indeed, the majority of Vietnamese words is built by semantic composition from about 7,000 syllables, which also have a meaning as isolated words. So the identification of word boundaries in a text is not a simple task, and ambiguities often appear. Beyond the presentation of the tested systems, we also propose a standard definition for word segmentation in Vietnamese, and introduce a reference corpus developed for the purpose of evaluating such a task. The results observed confirm that it can be relatively well treated by automatic means, although a solution needs to be found to take into account out-of-vocabulary words.

This paper describes the ARCADE II project, concerned with the evaluation of parallel text alignment systems. The ARCADE II project aims at exploring the techniques of multilingual text alignment through a fine evaluation of the existing techniques and the development of new alignment methods. The evaluation campaign consists of two tracks devoted to the evaluation of alignment at sentence and word level respectively. It differs from ARCADE I in the multilingual aspect and the investigation of lexical alignment.

In this paper, we present the first sizable grammar built for Vietnamese using LTAG, developed over the past two years, named vnLTAG. This grammar aims at modelling written language and is general enough to be both application- and domain-independent. It can be used for the morpho-syntactic tagging and syntactic parsing of Vietnamese texts, as well as text generation. We then present a robust parsing scheme using vnLTAG and a parser for the grammar. We finish with an evaluation using a test suite.