[PDF] Top 20 Fast Consensus Hypothesis Regeneration for Machine Translation

... original translation N-best list or translation forest; T n ( 1 ≤ n ≤ 4 ) are the sets of n-grams collected from translation N-best list or translation ... See full document

... chine translation accuracy by leveraging trans- lation consensus between multiple machine translation ...chine translation decoders, in our method mul- tiple machine ... See full document

... in MT. A heuristic is used in A* search to es- timate the cost of completing a partial hypothe- sis. A good heuristic makes it possible to accu- rately compare the value of different partial hy- potheses, and thus to ... See full document

... The most similar work that we know of is Le et al. (2012). Le’s basic procedure is to re-order the source to match the linear order of the target, and then segment the hypothesis into minimal bilin- gual phrase ... See full document

... average translation quality of a given sys- tem as an absolute indicator of its ...the consensus among different MT systems in the translations they ...multi- translation dataset or those produced by ... See full document

... for machine trans- lation output relative to the standard Viterbi ob- jective of maximizing model ...our fast decoding procedure can select output sentences based on distributions over entire forests of ... See full document

... multi-engine machine translation goes back to the early ...three translation systems to build a consensus ...used translation scores, language and other models to select one of the ... See full document

... translations. Consensus decoding, on the other hand, can be based on either single or multiple systems: single system based methods (Kumar and Byrne, 2004; Tromble et ...optimizing consensus models over the ... See full document

... of consensus over the many weighted derivations in a transla- tion ...the fast consen- sus decoding procedure of DeNero et ...a translation forest, then compute the expected count of each n-gram in ... See full document

... the consensus translation of the test corpus are differ- ent from the 5 original ...unseen consensus translations as gen- erated from the original translations is ...the consensus ... See full document

... Machine translation (MT) draws from several different disciplines, making it a complex sub- ject to teach. There are excellent pedagogical texts, but problems in MT and current algo- rithms for solving them ... See full document

... of machine translation (MT) research are ...a fast, convenient and above all consistent way using our tool and the corresponding graphical user ... See full document

... nal translation. 2) Hypothesis alignment: to build word-alignment between backbone and each hy- ...best translation from a confusion ...the hypothesis alignment presents the biggest challenge ... See full document

... ProbingPT and CompactPT produced identi- cal translations under the same decoder. In our tests 3 out of 200,000 sentences slightly differ in their translation. This is expected according to Junczys-Dowmunt (2012b) ... See full document

... Jan-Thorsten Peter, Hermann Ney, Ondˇrej Bojar, Ngoc-Quan Pham, Jan Niehues, Alex Waibel, Franck Burlot, François Yvon, M¯arcis Pinnis, Valters Sics, Joost Bast- ings, Miguel Rios, Wilker Aziz, Philip Williams, Frédéric ... See full document

... corpus, translation of words or phrases from either English language or Yorùbá language to its target language would become easier, It is a large and structured set of texts usually stored and processed in ... See full document

... Philipp Koehn, Hieu Hoang, Alexandra Birch, Chris Callison-Burch, Marcello Federico, Nicola Bertoldi, Brooke Cowan, Wade Shen, Christine Moran, Richard Zens, Chris Dyer, Ondrej Bojar, Alexandra Constantin, and Evan ... See full document

... We trained NMT models with depth of 16 in- cluding 25 LSTM layers and evaluated them mainly on the WMT’14 English-to-French translation task. This is the deepest topology that has been in- vestigated in the NMT ... See full document

... Neural Machine Translation (NMT) (Kalchbren- ner and Blunsom, 2013; Sutskever et al., 2014; Bahdanau et al., 2015) has recently gained popu- larity in solving the machine translation problem. ... See full document

... seconds translation time is slightly faster than last year’s fastest RNN-based submis- sions, but outperforms them by more than 4 BLEU and 10 BLEU points ... See full document