[PDF] Top 20 An Evaluation of Two Vocabulary Reduction Methods for Neural Machine Translation

... Most languages do not belong exclusively to one category of morphological typology. In fact, there are many languages where different morphological phenomena are observed to- gether. Based on how much such phenomena are ... See full document

... statistical machine translation (SMT) parame- ter tuning, for system comparison, and for assess- ing the progress during MT system ...MT evaluation metrics is usually assessed by computing their ... See full document

... artificial neural networks now have a great impact on translation ...entirely machine- translated into French and post-edited by several ...an evaluation of NMT is precisely the aim of the ... See full document

... automatic evaluation of machine translation (MT) has proven to be a very significant research ...automatic evaluation methods focus on the evalua- tion of the output of MT as they ... See full document

... recurrent neural network as encoder and is the state-of-the-art of pure NMT system ...the translation performance of patent sentences by applying approach of Bahdanau et ...phrase translation table ... See full document

... additional evaluation in order to as- sess the capacity of models in learning syntactic or morpho- logical dependencies using the Morpheval test suites, which consist of sentence pairs that differ by one ... See full document

... We did our study in the domain of news articles and professions. However, human corpora has a broad spectrum of categories, as an instance: in- dustrial, medical, legal that may rise other biases particular to each area. ... See full document

... We can see in the figure, that when N = 100K , where only the common words are used, we perform best using the NMT system. The PreMT system performs similar and the PBMT system performs clearly worse. If we now decrease ... See full document

... up Neural Machine Translation (NMT) decoding by shrinking run-time target ...with two shrinking approaches: Locality Sensi- tive Hashing (LSH) and word ...same methods improve BLEU by ... See full document

... For NMT, we further split the words into sub- words using byte pair encoding (BPE) (Sennrich et al., 2016c), which has been shown to be effec- tive for the rare word problem in NMT. Another motivation of using sub-words ... See full document

... three translation tasks: Machine Translation of News, Biomedical Translation, and Multimodal Machine Translation, two evaluation tasks: Metrics and Quality ... See full document

... Furthermore, machine translation services are primarily designed for translating sentences, rather than translating individual keyphrases as our current method ... 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

... and machine evaluation of machine translation; using NLP, automatic tools and techniques to study and extract meaningful patterns from interpreting, human translation, and manual ... See full document

... In addition, we used a rule augmentation method which is known as syntax-augmented machine translation (Zollmann and Venugopal, 2006). Because the tree-to-string SMT makes some constraints on extracting ... See full document

... automatic evaluation measure is to show that it correlates highly with human judgments in different evaluation ...MT evaluation (NIST ...automatic evaluation meth- ods, we created three ... See full document

... sentence-level vocabulary, which is very small compared with the full target vocab- ...the translation am- biguity, we generate those sentence-level vocab- ularies by utilizing word-to-word and phrase-to- ... See full document

... Anabel Rebollo, Kathy Yang, Jean Senellart, E- gor Akhanov, Patrice Brunelle, Aurelien Coquard, Yongchao Deng, Satoshi Enoue, Chiyo Geiss, Joshua Johanson, Ardas Khalsa, Raoum Khiari, Byeongil Ko, Catherine Kobus, Jean ... See full document

... of vocabulary items. The approach combines Bayesian and neural network methods to address learning at the word and sub-word ...spent two years as a postdoctoral researcher at Stanford ... See full document

... We adapt a convolutional neural network (CNN)- based sequence-to-sequence NMT with multi-hop attention mechanism between encoder and de- coder (Gehring et al., 2017). Our CNN architec- ture computes the encoder ... See full document