The paper presents a study of a challenging task in machine translation and crosslanguage information retrieval – translation of toponyms. Due to their linguistic and extra-linguistic nature, toponyms deserve a special treatment. The overall translation process includes two stages of processing: dictionary-based and out-ofvocabulary toponym translation. The latter is divided into three steps: s...

this paper was aimed at investigating the persian-speaking translation trainees perception of politeness of english request strategies. they judged the strategies for requesting (e.g. can, could, will, do, etc.) using the paired comparison method. the findings showed great divergence between the judgment of english native speakers with respect to the degree of politeness of 14 generic request s...

We investigate a range of crosslingual web retrieval tasks using the test suite of the CLEF 2005 WebCLEF track, which features a stream of known-item topics in various languages. Our main findings are: (i) straightforward indexing and retrieval is effective for mixed monolingual web retrieval; (ii) standard machine translation methods are effective for bilingual web retrieval; but (iii) standar...

This paper describes the USAARSHEFFIELD systems that participated in the Semantic Textual Similarity (STS) English task of SemEval-2015. We extend the work on using machine translation evaluation metrics in the STS task. Different from previous approaches, we regard the metrics’ robustness across different text types and conflate the training data across different subcorpora. In addition, we in...

We present PROTEST, a test suite for the evaluation of pronoun translation by MT systems. The test suite comprises 250 hand-selected pronoun tokens and an automatic evaluation method which compares the translations of pronouns in MT output with those in the reference translation. Pronoun translations that do not match the reference are referred for manual evaluation. PROTEST is designed to supp...

This study was an attempt to investigate the effect of lexicon-based debates on the felicity of lexical equivalents in translating literary texts by Iranian EFL learners.  To fulfill the purpose of this study, 59 university students, majoring in English Translation, were randomly assigned to the experimental and control groups from a total of 73 students based on their performance on a mock TOE...

This paper describes the hierarchical phrase-based machine translation system built jointly by the University of Edinburgh and the University of Munich (LMU) for the shared translation task at the ACL 2016 First Conference on Machine Translation (WMT16). The WMT16 Edinburgh/LMU system was trained for translation of news domain texts from English into Romanian. We participated in the shared task...

This position paper presents the recently started European collaboration project LetsMT!. This project creates a platform that gathers public and userprovided MT training data and generates multiple MT systems by combining and prioritizing this data. The project extends the use of existing state-of-the-art SMT methods that are applied to data supplied by users to increase quality, scope and lan...

Out-of-vocabulary (oov) words or phrases still remain a challenge in statistical machine translation especially when a limited amount of parallel text is available for training or when there is a domain shift from training data to test data. In this paper, we propose a novel approach to finding translations for oov words. We induce a lexicon by constructing a graph on source language monolingua...

This paper presents an approach to improving performance of statistical machine translation by automatically creating new training data for difficult to translate phenomena. In particular this contribution is targeted towards tackling the poor performance of a state-of-the-art system on negated sentences. The corpus expansion is achieved by high quality rephrasing of existing sentences to their...