Articles

Grammatical Framework (GF) is a meta-language for multilingual linguis- tic descriptions, which can be used to build rule-based interlingua MT ap- plications in natural sublanguage domains. The GF open-source package contains linguistic and computational resources to facilitate language en- gineering including: a resource grammar library for ten languages, a user …...

We present an intuitive technical framework for making Computer Assisted Translation (CAT) adaptable and more suitable for rapid application devel- opment. The framework is a client-server-based architecture that uses an approach similar to “message passing”, a technique widely used in computer science. We define a “translation object”, a structure holding …...

This paper investigates the use of morpho- syntactic information to reduce data- sparseness in statistical machine transla- tion from Spanish to English. In particular, word-alignment training is performed by applying different word transformations using lemmas and stems. It has been ob- served that stem-based training is better than lemma-based training …...

. In this paper, a fast automatic NP alignment technique developed for MetaMorpho TM is presented. MetaMorpho TM is an EBMT-based translation memory that stores not only full sentence pairs but also NP pairs in its database of translations. In order to fulfill speed requirements of a translation memory (segments …...

The Data-Oriented Translation (DOT) model – originally proposed in (Poutsma, 1998, 2003) and based on Data-Oriented Parsing (DOP) (e.g. (Bod, Scha, & Sima’an, 2003)) – is best described as a hybrid model of translation as it combines examples, linguistic information and a statisti- cal translation model. Although theoretically interesting, it …...

Translation of discontinuous phrases is a major challenge in Machine Trans- lation. Within METIS-II we developed a dictionary lookup strategy by mapping the items of a dictionary entry on non-adjacent words in an input text. Mapping is controlled through so-called contextual rejection, i.e. in- appropriate mappings are discarded if they …...

. The ready availability of free online machine translation (MT) systems has given rise to a problem in the world of language teaching in that students – especially weaker ones – use free online MT to do their translation homework. Apart from the pedagogic implications, one question of interest is …...

. We present an Online Server for Machine Translation Evaluation that offers improvements over the standard usage of the typical scoring scripts. Users are able to interactively define their own test sets, experiments and pre-processing steps. Several scores are automatically calculated for submitted translations and the hypotheses and scores are …...

One of the bottlenecks of example-based machine translation (EBMT) is to be able to amass automatically quantities of good examples. In our work in EBMT, we are investigating how far one can go by performing example extraction from parallel corpora using Probabilistic Translation Dictionaries to obtain example segmentation points. In …...

The Computer-Assisted Translation (CAT) paradigm tries to integrate hu- man expertise into the automatic translation process. In this paradigm, a human translator interacts with a translation system that dynamically offers a list of translations that best completes the part of the sentence that is being translated. This human-machine sinergy aims …...

We present two semi-supervised learning techniques to improve a state-of-the-art multi-lingual name tagger. For English and Chinese, the overall system obtains 1.7% - 2.1% improvement in F-measure, representing a 13.5% - 17.4% relative re- duction in the spurious, missing, and in- correct tags. We also conclude that simply relying upon …...

An unsupervised learning method, based on corpus linguistics and special lan- guage terminology, is described that can extract time-varying information from text streams. The method is shown to be ‘language-independent’ in that its use leads to sets of regular-expressions that can be used to extract the information in typologically distinct …...

Many information extraction (IE) systems rely on manually annotated training data to learn patterns or rules for extracting in- formation about events. Manually anno- tating data is expensive, however, and a new data set must be annotated for each domain. So most IE training sets are rel- atively small. Consequently, …...

Lexical Chains are powerful representa- tions of documents. In particular, they have successfully been used in the field of Automatic Text Summarization. How- ever, until now, Lexical Chaining algo- rithms have only been proposed for Eng- lish. In this paper, we propose a greedy Language-Independent algorithm that au- tomatically extracts …...

This paper presents a novel approach to the semi-supervised learning of Informa- tion Extraction patterns. The method makes use of more complex patterns than previous approaches and determines their similarity using a measure inspired by re- cent work using kernel methods (Culotta and Sorensen, 2004). Experiments show that the proposed …...

The automatic extraction of trend informa- tion from text documents such as news- paper articles would be useful for explor- ing and examining trends. To enable this, we used data sets provided by a workshop on multimodal summarization for trend in- formation (the MuST Workshop) to con- struct an automatic …...

Several recently reported techniques for the automatic acquisition of Information Extraction (IE) systems have used depen- dency trees as the basis of their extrac- tion pattern representation. These ap- proaches have used a variety of pattern models (schemes for representing IE pat- terns based on particular parts of the de- …...

AbstractWe examine a new, intuitive measure for evaluating machine-translation output that avoids the knowledge intensiveness of more meaning-based approaches, and the labor-intensiveness of human judgments. Translation Edit Rate (TER) measures the amount of editing that a human would have to perform to change a system output so it exactly matches …...

AbstractIn this paper, we discuss techniques to combine an interlingua translation framework with phrase-based statistical methods, for translation from Chinese into English. Our goal is to achieve high-quality translation, suitable for use in language tutoring applications. We explore these ideas in the context of a flight domain, for which we …...

AbstractWe present and empirically compare a range of novel probabilistic finite-state transducer (PFST) models targeted at two major natural language string transduction tasks, transliteration selection and cognate translation selection. Evaluation is performed on 10 distinct language pair data sets, and in each case novel models consistently and substantially outperform a …...