[PDF] Top 20 Sheffield Systems for the English Romanian WMT Translation Task

... WMT16 English-Romanian translation ...best translation hypothesis within a 1000 distinct n-best ...sampling translation candi- ...the task, with PRO obtaining better results from ... See full document

... • Sparse Features: For each source phrase, there is usually more than one corresponding translation option. Each different translation may be optimal in different contexts. Thus in our systems, ... See full document

... Automatic evaluation. Table 7 shows the val- ues of the BLEU and chrF++ automatic eval- uation metrics obtained by our systems on the newstest2019 test set. In order to assess the impact of the enhancements ... See full document

... In this section we will illustrate how we used the Marian toolkit to facilitate our own research across several NLP problems. Each subsection is meant as a showcase for different components of the toolkit and ... See full document

... chine translation systems for the WMT 2019 biomedical translation shared ...our systems on a combina- tion of out-of-domain and in-domain paral- lel corpora for six translation ... See full document

... From Tables 2 and 3 we can see that the back- translations gained a small improvement to our systems, specially when there has not been a pre- vious training over only true parallel data (sys1 in Table 2). This is ... See full document

... the WMT 2019 news translation shared task for English–Gujarati language pair within the translation task sub- ...machine translation (NMT) system which follows attention ... See full document

... back- translation technique for this ...machine translation for many lan- guage pairs. We train systems at subword ...SMT systems, mono- lingual sentences (for both Gujarati and ... See full document

... Machine Translation shared ...For task 1, we build on a standard sequence to sequence attention-based neural machine translation system (NMT) and investigate the utility of multimodal re-ranking ... See full document

... this translation task is considered, only a small development set of news- discusssions is ...our systems, we performed a 3-fold cross- validation, splitting the 1,500 in-domain sentences in two ... See full document

... date of f produced by our phrase-based decoder. Due to the limited time, this recurrent encoder- decoder-based (ReEnDe) feature was only em- ployed in the direction of English→German. It helped to improve ... See full document

... We present our experiments in the scope of the news translation task in WMT 2018, in direc- tions: English → German. The core of our sys- tems is the encoder-decoder based neural ma- chine ... See full document

... we create a mixed input for the NMT system con- sisting of both sentences by concatenating them. This scheme, however, may lead to errors when the source and target languages have a same word in surface, but with ... See full document

... lation task and showed that suffix separation sig- nificantly reduces data sparseness in the Bengali ...the WMT Hindi-to-English translation ...SMT systems on the both types of training ... See full document

... the English-Russian and Russian-English statistical machine translation (SMT) systems developed at Yandex School of Data Analysis for the shared translation task of the ACL 2013 ... See full document

... • Firstly, capitalisation statistics (ignoring first words) were taken from the unmodified Eu- roparl corpus and applied to each individual word in the automated translation. For ex- ample, there would be ... See full document

... MT systems of the two different paradigms (Pinnis et ...MT systems and asked to select, which system (NMT, SMT, or nei- ther) produces a better ...NMT systems produce better translations than the SMT ... See full document

... Same as last year, we train the model with separate vocabularies due to the Cyrillic nature of Russian alphabet. Therefore we use separate BPE models for source and target with 35k and 45k merge operations respectively. ... See full document

... validation translation less frequently and set a higher early-stopping threshold to allow the model iterate over the training data for several epochs; 2) we do not use shared vocabulary because of the different ... See full document

... The first step in system combination is gen- eration of confusion networks (CN) from I in- put translation hypotheses. We need pairwise alignments between the input hypotheses, and the alignments are obtained by ... See full document