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• W2149366535 abstract "The overwhelming majority of the languages in the world are spoken by less than 50 million native speakers, and automatic translation of many of these languages is less investigated due to the lack of linguistic resources such as parallel corpora. In the ACCURAT project we will work on novel methods how comparable corpora can compensate for this shortage and improve machine translation systems of under-resourced languages. Translation systems on eighteen European language pairs will be investigated and methodologies in corpus linguistics will be greatly advanced. We will explore the use of preliminary SMT models to identify the parallel parts within comparable corpora, which will allow us to derive better SMT models via a bootstrapping loop. State-of-the-art machine translation based on the statistical approach is a data-driven process. The quality and quantity of the training data is crucial for the performance of a translation system. However, the increasing amount of training corpora can still not meet the demand of automatic translation on different language pairs and in various domains. Rich data are mostly available for few languages and only certain domains. There are still a great number of underresourced languages. Thousands of languages are spoken by less than 50 million native speakers, with a big group of more than 200 languages that have between 1 and 50 million native speakers. Most of these languages are lacking sufficient linguistic resources. This brings difficulties to improve the translation qualities on these languages. For instance, the majority of the European languages are under-resourced and lack both parallel corpora and language technologies for MT. The project ACCURAT (Analysis and Evaluation of Comparable Corpora for Under-Resourced Areas of Machine Translation) will focus on developing and evaluating language pairs of English-Latvian, English-Lithuanian, English-Estonian, English-Greek, English-Croatian, Croatian-English, English-Romanian, English-Slovenian, Slovenian-English, English-German, German-English, German-Romanian, Romanian-German, Greek-Romanian, LithuanianRomanian, Romanian-Greek, Romanian-English and Latvian-Lithuanian. We also work on the language pair of German and English which is well investigated previously. This can help us find the impact of comparable corpora on translations between language pairs with both rich and poor resources. More details can be found in (Skadina et al., 2010). The participants include organizations of Tilde," @default.
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• W2149366535 title "Improving Machine Translation Performance Using Comparable Corpora" @default.
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