We have investigated the potential for improvement in target language morphology when translating into Swedish from English and German, by measuring the errors made by a state of the art phrase-based statistical machine translation system. Our results show that there is indeed a performance gap to be filled by better modelling of inflectional morphology and compounding; and that the gap is not ...

In this article, we describe system architecture, preparation of training data and discussion on experimental results of the EIWA group in the NTCIR-10 Patent Translation Task. Our system is combining rule-based machine translation and statistical postediting. The thing about our new system compared with NTCIR-9 PatentMT task is to implement automatic selecting method from multiple translations...

We explore six challenges for neural machine translation: domain mismatch, amount of training data, rare words, long sentences, word alignment, and beam search. We show both deficiencies and improvements over the quality of phrasebased statistical machine translation.

translation, whose first traces date back at least to 3000 bc (newmark, 1988), has always been considered time-consuming and labor-consuming. in view of this, experts have made numerous efforts to develop some mechanical systems which can reduce part of this time and labor. the advancement of computers in the second half of the twentieth century paved the ground for the invention of machine tra...

Objectives: Various instruments and methods evaluate addiction to the Internet, mobile, and smartphone use. Subject-reported outcome measures, such as the smartphone addiction scale (SAS) assess such addiction. The objectives of this study were to cross-culturally adapt the SAS into Persian (SAS-Pr) and to evaluate the properties of reliability and validity in the Persian setting. Methods: The...

We describe the machine translation systems developed at the National Research Council of Canada (NRC) for the RussianEnglish and Chinese-English news translation tasks of the Second Conference on Machine Translation (WMT 2017). We conducted several experiments to explore the best baseline settings for neural machine translation (NMT). In the RussianEnglish task, to our surprise, our bestperfor...

Neural machine translation (NMT) approaches have improved the state of the art in many machine translation settings over the last couple of years, but they require large amounts of training data to produce sensible output. We demonstrate that NMT can be used for low-resource languages as well, by introducing more local dependencies and using word alignments to learn sentence reordering during t...

This paper presents a rule-based reordering approach for English-Hindi machine translation. We have used the concept of pada, from Pān. inian Grammar to frame the reordering rules. A pada is a word form which is ready to participate in a sentence. The rules are generic enough to apply on any English-Indian language pair. We tested the rules on English-Hindi language pair and obtained better com...