[PDF] Top 20 Unsupervised Tokenization for Machine Translation

... makes tokenization in English usu- ally ...chine translation, one token should not necessarily correspond to one morphological unit, but rather should reflect the morphological units and writing system of ... See full document

... based as criterion with a more efficient greedy algo- rithm. Chen (2013) proposes a compression-based method using MDL and improve the performance of monolingual segmentation. Argamon et al. (2004) use an efficient ... See full document

... There are various methods for extracting sentence pairs from monolingual corpora. However, most of them rely on the availability of document-level information, in comparable corpora for instance, and usually for one ... See full document

... because unsupervised NMT methods suffer from the noise problem while PBSMT is inherently defi- cient in fluency just as the case study in ...by unsupervised NMT, so that even PBSMT could not distinguish ... See full document

... Previous zero-shot NMT work compensates for a lack of source/target parallel data by either using source/pivot parallel data, extremely large monolingual data, or artificially generated data. These requirements and ... See full document

... Method 2: provides n-best transliterations to a monotonic decoder that uses a monolingual language model and a transliteration phrase- translation table to rescore transliterations. We carry forward the 4 ... See full document

... of unsupervised determination of the optimal morphological segmentation for statistical machine translation (SMT) and propose a segmentation metric that takes into account both sides of the SMT ... See full document

... an unsupervised phrase-based statistical machine translation system (Lample et ...extract translation candidates by taking the 100 nearest-neighbors of each source phrase, and score them with ... See full document

... and unsupervised NMT system were trained with German monolingual data which was not compound ...original unsupervised NMT system are trained with com- pound split German monolingual ... See full document

... ral Machine Translation (NMT) under the following three conditions posed by real- world application ...this unsupervised multi-domain setting, we explore an ef- ficient instance-based adaptation ... See full document

... to machine translation (Wu et ...neural machine translation (NMT) employs the encoder- decoder architecture, where the encoder reads the source sentence and produces its representation which ... See full document

... for machine transla- tion has been well studied in the recent ...an unsupervised discriminative train- ing framework to incorporate the usually plen- tiful target-language monolingual data by us- ing a ... See full document

... using unsupervised Vecmap (Artetxe et ...backward translation systems, instead of using only either forward (Marie and Fujita, 2018b) or backward translations (Artetxe et ... See full document

... get unsupervised cross-lingual n-gram embeddings of them, from which we infer n-gram translation tables (source-to-target and target-to- ...n-gram translation pairs inferred in this way have proven ... See full document

... neural machine translation (NMT) has recently proven success- ful (Eriguchi et ...an unsupervised tree-to-sequence (tree2seq) model for neural machine translation; this model is able to ... See full document

... sentence-level translation prob- abilities using the lexical translation probabil- ities learned by mgiza during the training of our SMT ...each translation direc- tion were also ...the ... See full document

... the unsupervised CDLM training suffer from this unrelated limitation of the tuning procedure, we give it too the benefit of being able to compute risk on Set3 using y plus its 15 ... See full document

... standard machine transla- tion benchmarks using monolingual corpora ...on unsupervised cross-lingual embedding mappings, which independently train word embeddings in two languages and learn a linear ... See full document

... Recently, motivated by the success of cross- lingual embeddings (Artetxe et al., 2016; Zhang et al., 2017; Conneau et al., 2017), several works have tried to train NMT or SMT models using un- supervised setting, in which ... See full document

... For model selection, we stop training when the model achieves no improvement for the tenth e- valuation on the development set, which is com- prised of 3000 source and target sentences extract- ed randomly from the ... See full document