This paper addresses the problem of reliably measuring productivity gains by professional translators working with a machine translation enhanced computer assisted translation tool. In particular, we report on a field test we carried out with a commercial CAT tool in which translation memory matches were supplemented with suggestions from a commercial machine translation engine. The field test ...

objectives : bayley scales of infant & toddler development is a well-known diagnostic developmental assessment tool for children aged 1–42 months. our aim was investigating validity & reliability of this scale in persian speaking children. materials & methods: the method was descriptive-analytic. translation- back translation and cultural adaptation was done. content & face validity of tranlate...

This paper describes the development of a Japanese-English and English-Japanese translation system for the NTCIR-10 Patent MT tasks. The MT system is based on the provided training data and Moses decoder. We report our first attempt on statistical machine translation for these pairs of languages and the Patent domain.

Sentence-aligned bilingual texts are a crucial resource to build statistical machine translation (SMT) systems. In this paper we propose to apply lightly-supervised training to produce additional parallel data. The idea is to translate large amounts of monolingual data (up to 275M words) with an SMT system, and to use those as additional training data. Results are reported for the translation f...

This paper proposes a method for handling out-of-vocabulary (OOV) words that cannot be translated using conventional phrase-based statistical machine translation (SMT) systems. For a given OOV word, lexical approximation techniques are utilized to identify spelling and inflectional word variants that occur in the training data. All OOV words in the source sentence are replaced with appropriate ...

We use referential translation machines (RTM) for quality estimation of translation outputs. RTMs are a computational model for identifying the translation acts between any two data sets with respect to interpretants selected in the same domain, which are effective when making monolingual and bilingual similarity judgments. RTMs achieve top performance in automatic, accurate, and language indep...

Translating into morphologically rich languages is difficult. Although the coverage of lemmas may be reasonable, many morphological variants cannot be learned from the training data. We present a statistical translation system that is able to produce these inflected word forms. Different from most previous work, we do not separate morphological prediction from lexical choice into two consecutiv...

Accuracy of dependency parsers is one of the key factors limiting the quality of dependencybased machine translation. This paper deals with the influence of various dependency parsing approaches (and also different training data size) on the overall performance of an English-to-Czech dependency-based statistical translation system implemented in the Treex framework. We also study the relationsh...

Some Statistical Machine Translation systems never see the light because the owner of the appropriate training data cannot release them, and the potential user of the system cannot disclose what should be translated. We propose a simple and practical encryption-based method addressing this barrier.

Transitional expressions provide glue that holds ideas together in a text and enhance the logical organization, which together help improve readability of a text. However, in most current statistical machine translation (SMT) systems, the outputs of compound-complex sentences still lack proper transitional expressions. As a result, the translations are often hard to read and understand. To addr...