[PDF] Top 20 Massively Multilingual Neural Machine Translation

... our massively multilingual models and bilingual baselines when evaluated ...the translation directions the model is trained on are into English, this leaves less capac- ity for the other target ... See full document

... To evaluate and improve the wordnets for the targeted under-resourced Dravidian languages, Chakravarthi et al. (2018) followed the approach of Arcan et al. (2016), which uses the existing trans- lations of wordnets in ... See full document

... and multilingual modeling (Firat et ...simple multilingual modeling (MultiNMT) was proposed by Johnson et ...of multilingual data to improve NMT for all languages ... See full document

... based neural machine translation has become de facto standard in neural translation literatures re- cently (Jean et ...report translation perplex- ity, which is not a widely used ... See full document

... the translation, once the added modules are trained the zero-shot translation is performed without gener- ating the language used for training as the sentence representations in the shared space are ... See full document

... Multimodal machine translation is the task of translating from a source text into the target language using information from other ...manual translation of English descriptions from the Flickr30K ... See full document

... Prior work has examined data selection from the view of domain adaptation, selecting good train- ing data from out-of-domain text to improve in- domain performance. In general, these methods select data that score above ... See full document

... and translation from these to Hindi consti- tute the child ...Initiative) multilingual parallel corpus (Jha, 2010) 1 spans multiple Indian languages from the health and tourism ... See full document

... Transfer from multiple source languages: Previous work has shown the improvements of multi-source transfer in NER (T¨ackstr¨om, 2012; Fang et al., 2017; Enghoff et al., 2018), POS tag- ging (Snyder et al., 2009; Plank ... See full document

... In this paper, we use the framework of neural machine translation to learn joint sentence representations across six very different languages. Our aim is that a rep- resentation which is independent ... See full document

... French-to-English translation, a source sentence may be tagged with opt src f1 opt tgt e0, denoting that it is translating from version “f1” of French data to version “e0” of En- glish ...12 translation ... See full document

... The language pair schedule used during train- ing is crucial for learning an effective sentence representation. We provide the details in Algo- rithm 1. In our initial experiments, we cycled through 10 language pairs ... See full document

... Multilingual neural machine translation (NMT), which translates multiple languages using a single model, is of great practi- cal importance due to its advantages in simplifying the training ... See full document

... As can be seen from Table 7, for the English↔X directions, all three models show comparable scores. On the Ru↔{Be, Uk} directions, the “Zero-Shot” model already achieves relatively high BLEU scores for all directions ... See full document

... years, neural networks have emerged as a common way to use data from several languages in a single ...zero-shot neural ma- chine translation system (Johnson et ...for translation between ... See full document

... Chinese-English Translation Table 1 summarizes the BLEU scores of different systems on the Chinese-English translation ...improves translation quality in terms of BLEU on most cases, and ob- tains ... See full document

... We analyze the performance of our techniques on a closed- and open-domain of the WMT 2018 German ↔ English news translation task. We provide qualitative and quantitative evidence of the detrimental behaviours and ... See full document

... of neural networks follows two main strategies: (i) model parallel evalu- ates different model layers on different work- ers (Coates et ...ral machine translation systems have been recently trained ... 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 systems and ... See full document

... Machine translation using deep neural networks achieved great success with sequence-to- sequence models Sutskever et ...current neural networks (RNNs) with LSTM cells Hochreiter and ... See full document