German compound words pose special problems to statistical machine translation systems: the occurence of each of the components in the training data is not sufficient for successful translation. Even if the compound itself has been seen during training, the system may not be capable of translating it properly into two or more words. If German is the target language, the system might generate on...

Lexical chains provide a representation of the lexical cohesion structure of a text. In this paper, we propose two lexical chain based cohesion models to incorporate lexical cohesion into document-level statistical machine translation: 1) a count cohesion model that rewards a hypothesis whenever a chain word occurs in the hypothesis, 2) and a probability cohesion model that further takes chain ...

This work presents improvements of a large-scale Arabic to French statistical machine translation system over a period of three years. The development includes better preprocessing, more training data, additional genre-specific tuning for different domains, namely newswire text and broadcast news transcripts, and improved domain-dependent language models. Starting with an early prototype in 200...

Pronouns are frequently omitted in pro-drop languages, such as Chinese, generally leading to significant challenges with respect to the production of complete translations. To date, very little attention has been paid to the dropped pronoun (DP) problem within neural machine translation (NMT). In this work, we propose a novel reconstruction-based approach to alleviating DP translation problems ...

In this paper we describe an attempt to compare how relatedness of languages can influence the performance of statistical machine translation (SMT). We apply the Moses toolkit on the Czech-English-Russian corpus UMC 0.1 in order to train two translation systems: Russian-Czech and English-Czech. The quality of the translation is evaluated on an independent test set of 1000 sentences parallel in ...

The present research aimed to investigate the effect of background Mozart Classical music on translator students' performance. In this study, the researchers focused not only on the relationship between music and translation but also on the relationship between music and personality traits. The main question this study tried to answer was whether using background music might enhance students' t...

The study was aimed at investigating the effectiveness of methods of teaching Translation Courses (TCs) used by Iranian instructors on English-major students’ translation proficiency development. To this end, 156 homogeneous students were selected as the participants to undergo quantitative and qualitative data collection simultaneously through a convergent parallel mixed methods design. The da...

Many languages use honorifics to express politeness, social distance, or the relative social status between the speaker and their addressee(s). In machine translation from a language without honorifics such as English, it is difficult to predict the appropriate honorific, but users may want to control the level of politeness in the output. In this paper, we perform a pilot study to control hono...

Chiang’s hierarchical phrase-based (HPB) translation model advances the state-of-the-art in statistical machine translation by expanding conventional phrases to hierarchical phrases – phrases that contain sub-phrases. However, the original HPB model is prone to overgeneration due to lack of linguistic knowledge: the grammar may suggest more derivations than appropriate, many of which may lead t...

We describe an experiment in rapid development of a statistical machine translation (SMT) system from scratch, using limited resources: under this heading we include not only training data, but also computing power, linguistic knowledge, programming effort, and absolute time.