We present a novel approach to improve word alignment for statistical machine translation (SMT). Conventional word alignment methods allow discontinuous alignment, meaning that a source (or target) word links to several target (or source) words whose positions are discontinuous. However, we cannot extract phrase pairs from this kind of alignments as they break the alignment consistency constrai...

While the effect of domain variation on Penntreebank-trained probabilistic parsers has been investigated in previous work, we study its effect on a Penn-Treebank-trained probabilistic generator. We show that applying the generator to data from the British National Corpus results in a performance drop (from a BLEU score of 0.66 on the standard WSJ test set to a BLEU score of 0.54 on our BNC test...

The hierarchical Pitman-Yor process-based smoothing method applied to language model was proposed by Goldwater and by Teh; the performance of this smoothing method is shown comparable with the modified Kneser-Ney method in terms of perplexity. Although this method was presented four years ago, there has been no paper which reports that this language model indeed improves translation quality in ...

The advent of the attention mechanism in neural machine translation models has improved the performance of machine translation systems by enabling selective lookup into the source sentence. In this paper, the efficiencies of translation using bidirectional encoder attention decoder models were studied with respect to translation involving morphologically rich languages. The English–Tamil langua...

In this paper, we present the results of our investigation into phrase-based statistical machine translation from English into Turkish – an agglutinative language with very productive inflectional and derivational word-formation processes. We investigate different representational granularities for morphological structure and find that (i) representing both Turkish and English at the morpheme-l...

Translation systems are generally trained to optimize BLEU, but many alternative metrics are available. We explore how optimizing toward various automatic evaluation metrics (BLEU, METEOR, NIST, TER) affects the resulting model. We train a state-of-the-art MT system using MERT on many parameterizations of each metric and evaluate the resulting models on the other metrics and also using human ju...

Dialects and standard forms of a language typically share a set of cognates that could bear the same meaning in both varieties or only be shared homographs but serve as faux amis. Moreover, there are words that are used exclusively in the dialect or the standard variety. Both phenomena, faux amis and exclusive vocabulary, are considered out of vocabulary (OOV) phenomena. In this paper, we prese...

Parallel corpus is a key component of statistical and Neural Machine Translation (NMT). While most research focuses on machine translation, creation studies are limited for many languages no paper Mizo–English exists yet. A high-quality parallel required Natural Language Processing (NLP) activities including Chatbots, Transliteration, Cross-Language Information Retrieval. This work aims to inve...

Les colorants bleus sont utilisés en médecine et chirurgie de longue date. Injectés dans les tissus, ils dirigés vers le système lymphatique, ce qui permet l’identification directe des ganglions sentinelles lors chirurgies oncologiques, cadre d’un cancer du sein ou mélanome. Trois d’entre eux à cette fin, soit bleu patenté, isosulfan méthylène. Ils également pour marquer tissus chromoendoscopie...