Total Articles: 38870

nan

Publication: TIPSTER (2001)

DOI: nan

Paper ID: 17137

AbstractThis paper summarizes the current status of version 2 of the Open Lexicon Interchange Format (OLIF). As a natural extension of the OLIF prototype (OLIF version 1), version 2 has been modified with respect to content and formalization (e.g., it is now XML-compliant). These enhancements now make it possible to …...

nan

Publication: TIPSTER (2001)

DOI: nan

Paper ID: 17138

AbstractThis paper takes a practical look at ways of combining language engineering tools to produce more accurate, “more human” automatic translations. Whilst specific products are discussed, the author believes that the methodology could be successfully implemented with different sets of tools....

nan

Publication: TIPSTER (2001)

DOI: nan

Paper ID: 17139

AbstractThe Pan American Health Organization (PAHO) is proud to present the latest release of its fully automatic Spanish-to-English and English-to-Spanish machine translation systems. SPANAM and ENGSPAN have been ported to the 32-bit Windows platform. The bilingual graphical user interface provides easy access to all the features of the system. The …...

nan

Publication: TIPSTER (2001)

DOI: nan

Paper ID: 17140

AbstractIn this paper, we present a way to integrate bilingual lexicons into an operational probabilistic translation assistant (TransType). These lexicons could be any resource available to the translator (e.g. terminological lexicons) or any resource statistically derived from training material. We describe a bilingual lexicon acquisition process that we developped and …...

nan

Publication: TIPSTER (2001)

DOI: nan

Paper ID: 17141

AbstractThis paper describes KORTERM’s test suite and their practicability. The test-sets have been being constructed on the basis of fine-grained classification of linguistic phenomena to evaluate the technical status of English-to-Korean MT systems systematically. They consist of about 5000 test-sets and are growing. Each test-set contains an English sentence, a …...

nan

Publication: TIPSTER (2001)

DOI: nan

Paper ID: 17142

AbstractThe DARPA MT evaluations of the early 1990s, along with subsequent work on the MT Scale, and the International Standards for Language Engineering (ISLE) MT Evaluation framework represent two of the principal efforts in Machine Translation Evaluation (MTE) over the past decade. We describe a research program that builds on …...

nan

Publication: TIPSTER (2001)

DOI: nan

Paper ID: 17143

AbstractMost MT lexicography is devoted to developing rules of the kind, “in context C, translate source-language word S as target-language word T”. Very many such rules are required, producing them is laborious, and MT companies standardly spend large sums on it. We present the WASP-Bench, a lexicographer's workstation for the …...

nan

Publication: TIPSTER (2001)

DOI: nan

Paper ID: 17144

AbstractJapanese and Uighur languages are agglutinative languages and they have many syntactical and morphological similarities. And roughly speaking, we can translate Japanese into Uighur sequentially by replacing Japanese words with corresponding Uighur ones after morphological analysis. However, we should translate agglutinated suffixes carefully to make correct translation, because they play …...

nan

Publication: TIPSTER (2001)

DOI: nan

Paper ID: 17145

AbstractThis paper describes a method for disambiguating word senses by using semi-automatically constructed ontology. The ontology stores rich semantic constraints among 1,110 concepts, and enables a natural language processing system to resolve semantic ambiguities by making inferences with the concept network of the ontology. In order to acquire a reasonably …...

nan

Publication: TIPSTER (2001)

DOI: nan

Paper ID: 17146

AbstractIn this paper we present an overview of an approach developed at Microsoft Research to generate strings for named entities such as places and dates. This approach uses abstract representations as input. We first provide an overview of our system to identify named entities in text. Next we present our …...

nan

Publication: TIPSTER (2001)

DOI: nan

Paper ID: 17147

AbstractPatent summaries are machine-translated using bilingual term entries extracted from parallel texts for evaluation. The result shows that bilingual term entries extracted from 2,000 pairs of parallel texts which share a specific domain with the input texts introduce more improvements than a technical term dictionary with 38,000 entries which covers …...

nan

Publication: TIPSTER (2001)

DOI: nan

Paper ID: 17149

AbstractThis paper describes a prototype Japanese-to-Chinese automatic language translation system. ALT-J/C (Automatic Language Translator - Japanese-to-Chinese) is a semantic transfer based system, which is based on ALT-J/E (a Japanese-to-English system), but written to cope with Unicode. It is also designed to cope with constructions specific to Chinese. This system has …...

nan

Publication: TIPSTER (2001)

DOI: nan

Paper ID: 17150

AbstractThis paper presents a multilingual Natural Language Generation system that produces technical instruction texts in Bulgarian, Czech and Russian. It generates several types of texts, common for software manuals, in two styles. We illustrate the system’s functionality with examples of its input and output behaviour. We discuss the criteria and …...

nan

Publication: TIPSTER (2001)

DOI: nan

Paper ID: 17151

AbstractIn this paper we present a methodology for automating the evaluation of the grammatical coverage of machine translation (MT) systems. The methodology is based on the importance of unfolded grammatical structures, which represent the most basic syntactic pattern for a sentence in a given language. A database of unfolded grammatical …...

nan

Publication: TIPSTER (2001)

DOI: nan

Paper ID: 17152

AbstractMachine Translation (MT) systems that process unrestricted text should be able to deal with words that are not found in the MT lexicon. Without some kind of recognition, the parse may be incomplete, there is no transfer for the unfound word, and tests for transfers for surrounding words will often …...

nan

Publication: TIPSTER (2001)

DOI: nan

Paper ID: 17153

AbstractThe semantics of verbs implies, as is known, a great number of difficulties, when it is to be represented in a computational lexicon. The Slavic languages are especially challenging in respect of this task because of the huge complexity of verbs, where the stems are combined with prefixes indicating aspect …...

nan

Publication: TIPSTER (2001)

DOI: nan

Paper ID: 17154

AbstractThe increasing interest in the statistical approach to Machine Translation is due to the development of effective algorithms for training the probabilistic models proposed so far. However, one of the open problems with statistical machine translation is the design of efficient algorithms for translating a given input string. For some …...

nan

Publication: TIPSTER (2001)

DOI: nan

Paper ID: 17155

AbstractWe present an automated, system-internal evaluation technique for linguistic representations in a large-scale, multilingual MT system. We use machine-learned classifiers to recognize the differences between linguistic representations generated from transfer in an MT context from representations that are produced by "native" analysis of the target language. In the MT scenario, …...

nan

Publication: TIPSTER (2001)

DOI: nan

Paper ID: 17156

AbstractIn Japanese constructions of the form [N1 no Adj N2], the adjective Adj modifies either N1 or N2. Determing the semantic dependencies of adjective in such phrase is an important task for machine translation. This paper describes a method for determining the adjective dependency in such constructions using decision lists, …...

nan

Publication: TIPSTER (2001)

DOI: nan

Paper ID: 17157

AbstractThis paper describes an evaluation experiment designed to determine groups of subjects who prefer reading MT outputs to reading the original text. Our approach can be applied to any language pairs, but we will explain the methodology by taking English to Japanese translation as an example. In the case of …...