[PDF] Top 20 Controlling Text Complexity in Neural Machine Translation

... monolingual text simpli- fication aligner for cross-lingual ...articles machine translated into English by Google ...MASSAlign. Translation quality is high for this language pair, and even noisy ... See full document

... three neural machine translation tasks and one text summarization task show that our method outperforms conventional MLE loss on all these tasks and achieves promising BLEU scores on WMT14 ... See full document

... in machine translation and NLP has focused on readability assessment and text simpli- ...document text, whereas Ciobanu et ...for text simplification, Hardmeier et ...for text ... See full document

... the text being translated, as can be seen in the scores along the diagonal in Table ...list, translation quality improves by +0.5 BLEU on informal text, ...neutral text, and remains constant ... See full document

... syllable-based neural machine translation model, "sylbreak" is used to segment the Myanmar sentence into syllable ...(Burmese) text encoded with Unicode ... See full document

... The English word goalie is not translated to the correct German word Torwart, but to the German word Gott, which means god. One problem could be that we need to limit the vocabulary size in order to train the model ... See full document

... language 1 (Tillman, 2001), (Wang, 1997), (Ger- mann et al., 2003), (Udupa et al., 2004). The models are independent of the language pair and therefore, can be used to build a translation sys- tem for any language ... See full document

... We test the performance of the proposed text de- noising method on three downstream tasks: neural machine translation, natural language inference, and paraphrase detection. All experiments are ... See full document

... First of all, we evaluate the overall translation accuracy of each NMT system and production system on the concatenated data (ITEM+TEXT). Table 2 reports the case-sensitive sacreBLEU scores of the NMT ... See full document

... Neural machine translation has significantly pushed forward the quality of the ...ness. Neural models are trained on large text corpora which contain biases and ...in neural ma- ... See full document

... with neural machine translation without using parallel corpora, ...matching translation in the other ...word translation dictionary learned in an unsuper- vised way (Conneau et ...back ... See full document

... lators 8 maintained that they clearly recognised NMT chunks and segments even if ‘automated translation’ was not explicitly signaled in the CAT tool. Only three said they could not tell whether NMT had been used. ... See full document

... Other methods focus on how to reduce the pa- rameters trained by the model (See et al., 2016). They show that with a pruning technique, 40-60% of the parameters can be pruned out. Similar meth- ods are proposed to reduce ... See full document

... Development began focused on neural machine translation and so Tensor2Tensor includes many of the most successful NMT models and standard datasets. It has since added support for other task types as ... See full document

... Kingma et al. (2014) revisit the approach to semi- supervised learning with generative models and fur- ther develop new models that allow effective gen- eralization from a small labeled dataset to a large unlabeled ... See full document

... 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 ... See full document

... (1) controlling all sentences to active/passive voices, (2) controlling each sentence to the same voice as the reference sentence, and (3) predicting the voice using only the source ...Japanese-English ... See full document

... for controlling the level of formality of Japanese output in English-to-Japanese neural machine translation ...parallel text to train an English-Japanese NMT model capable of pro- ... See full document

... the translation quality in all cases, although there are still considerable differences among the proposed ...Model Complexity The proposed models introduce a few parameters to the NMT base- line system ... See full document

... in neural machine transla- ...ral machine translation, in terms of out- put length, bidirectional decoding, domain adaptation, and unaligned target word gen- ... See full document