[PDF] Top 20 Neural Machine Translation Decoding with Terminology Constraints

... target-side constraints for do- main adaptation via ...between constraints and the source words they cover, correct constraint placement is not guaranteed and the corresponding source words may be ... See full document

... We recall Table 5 where we see that the man- ual evaluator has marked 12 term translations with STC since in those cases the PB-SMT system copied source terms (or a part of source terms) verbatim into the target. In ... See full document

... 2. For our word alignment method, we find that only the candidate list derived from lexical translation table of IBM model 4 is adequate to achieve good BLEU/speedup trade-off for decoding on GPU. There is ... See full document

... English-to-Japanese translation task in ...English-to-Japanese translation shows that the character-based decoder does not outperform the word-based decoder but exhibits two promising properties: 1) It ... See full document

... on neural language models has proposed including various types of extra infor- mation, such as topic, genre or document context (Mikolov and Zweig, 2012; Aransa et ... See full document

... forced decoding algorithm, which is based on the standard phrase-based decoding algorithm and integrates new types of translation rules (deleting a source word or inserting a target ...forced ... See full document

... phrase-based decoding (Koehn et ...of constraints feasi- ble with GPU-based ...statistical machine translation seeks to find the output sequence, y, that maximizes ˆ the probability of a ... See full document

... Two approaches can be used to provide addi- tional information to the encoder-decoder model, word-level methods and sentence-level meth- ods. Word-level methods encode the addi- tional information as a vector (embedding) ... See full document

... Together with different findings that will be dis- cussed in the next sections, there are two main contributions in this paper. We redesigned and tuned the NMT framework for translating into MRLs. It is quite challenging ... See full document

... Le, Mohammad Norouzi, Wolfgang Macherey, Maxim Krikun, Yuan Cao, Qin Gao, Klaus Macherey, Jeff Klingner, Apurva Shah, Melvin Johnson, Xiaobing Liu, ukasz Kaiser, Stephan Gouws, Yoshikiyo Kato, Taku Kudo, Hideto Kazawa, ... See full document

... If our sole objective is to get a good approxi- mation to p(y | x), we should just use a single n-gram model q ∗ whose order n is as large as pos- sible, given computational constraints. This may be regarded as ... See full document

... A*) decoding algorithm is a kind of best-first search which was first intro- duced in the domain of speech recognition (Je- linek, ...modern terminology, a priority queue), the decoder conducts an ordered ... See full document

... bidirectional decoding (Liu et ...agent decoding from left to right (L2R) while the other decoding in opposite direction ...the translation models by introducing a regularization term into the ... See full document

... two decoding objectives for two ...evaluating translation systems) and log-likelihood (the most widely used learning criterion for neural machine ...greedy decoding and beam ...greedy ... See full document

... malization, but found it performed slightly worse. The merged partial hypotheses can be stored, and by assuming that their future predictions will be the same as their mergers, a lattice-like trans- lation graph can be ... See full document

... To the best of our knowledge, Goldberg et. al. (2012) first define the concept of dynamic oracle and propose an online algorithm for parsing problems, , which provides a set of optimal transitions for every valid parser ... See full document

... in translation, as it will be bringing different biases and making largely independent prediction errors to those of the left-to-right ...statistical machine translation by Watanabe and Sumita ... See full document

... general translation quality, allowing to rank them as ...the translation from the fused sys- tem is better than the baseline, and they consider the quality of both translations to tie 19% of the ... See full document

... custom terminology into neural machine trans- lation at run ...the decoding algo- rithm in order to constrain the output to in- clude run-time-provided target ...constrained decoding ... See full document

... This section describes one implementation of the transformation function Ψ that we will show leads to improved fluency of machine translation out- put. This transformation is based on n-gram cov- erage in a ... See full document