[PDF] Top 20 Response based Learning for Grounded Machine Translation
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Response based Learning for Grounded Machine Translation
... is response-based ...a response-driven learning framework for the area of semantic parsing: Here a meaning representation is “tried out” by itera- tively generating system outputs, receiving ... See full document
11
Confidence based Active Learning Methods for Machine Translation
... and machine translated texts, and an often small number (a few hundreds) of examples of translations labelled for quality by humans to train a machine learning al- gorithm to predict such quality ... See full document
6
Competence based Curriculum Learning for Neural Machine Translation
... specialized learning rate schedules and large batch ...curriculum learning framework for NMT that reduces training time, reduces the need for spe- cialized heuristics or large batch sizes, and re- sults in ... See full document
11
Active Learning for Statistical Phrase based Machine Translation
... active learning for SMT for domain adaptation and low-density/low-resource languages, there has been very little work published on this ...improve translation output in the de- ... See full document
9
Prediction of Learning Curves in Machine Translation
... Based on our prior knowledge of the problem, we limit the search for a suitable F to families that satisfies the following conditions- monotonically in- creasing, concave and bounded. The first condition just says ... See full document
9
A Multi Task Architecture on Relevance based Neural Query Translation
... multi-task learning approach to train a Neural Machine Translation (NMT) model with a Relevance-based Auxiliary Task (RAT) for search query ...task learning architecture that achieves ... See full document
6
Machine Learning for Hybrid Machine Translation
... In previous years, it turned out that the alignment of the candidate translations to the source contained too many errors. In this version of our system, we thus changed the alignment method that connects the other ... See full document
5
Comparing a Hand crafted to an Automatically Generated Feature Set for Deep Learning: Pairwise Translation Evaluation
... of machine translation (MT) has proven to be a very significant research ...for learning to classify parallel translations, using linguistic in- formation, of two MT model outputs and one human ... See full document
9
Learning from Chunk based Feedback in Neural Machine Translation
... Mart´ın Abadi, Ashish Agarwal, Paul Barham, Eugene Brevdo, Zhifeng Chen, Craig Citro, Greg S. Cor- rado, Andy Davis, Jeffrey Dean, Matthieu Devin, Sanjay Ghemawat, Ian Goodfellow, Andrew Harp, Geoffrey Irving, Michael ... See full document
6
Reinforcement Learning based Curriculum Optimization for Neural Machine Translation
... ral machine translation ...inforcement learning to learn one automati- cally, jointly with the NMT system, in the course of a single training ... See full document
8
Online Learning for Statistical Machine Translation
... online learning in SMT, we provide a much more detailed explanation of the different online update ...technique based on stochastic error correction models described in Ortiz-Mart´ınez ...online ... See full document
41
Graph based Learning for Statistical Machine Translation
... The synthetic nodes and edges need to be added to prevent the label propagation algorithm from con- verging to the trivial solution that assigns r = 1 to all points in the graph. This choice is theoretically motivated—a ... See full document
9
NICT’s participation to WAT 2019: Multilingualism and Multi step Fine Tuning for Low Resource NMT
... Neural machine translation (NMT) (Cho et ...alignments, translation rules, and complicated decoding algorithms, which are the characteris- tics of phrase-based statistical machine ... See full document
5
Response based Learning for Machine Translation of Open domain Database Queries
... the response-based learner and defines the final evaluation criterion, the challenge of the presented work lies in scaling the seman- tic parser to the lexical diversity of open-domain databases such as ... See full document
6
A Framework of Translator From English Speech To Sanskrit Text
... uses learning based speech recognition technique. And for translation it uses rule based machine ...for translation of similar ... See full document
9
Transductive learning for statistical machine translation
... the translation direction p(s | t), (b) one or several n-gram language model(s) trained with the SRILM toolkit (Stolcke, 2002); in the experi- ments reported here, we used 4-gram models on the NIST data, and a ... See full document
8
NAVER Machine Translation System for WAT 2015
... We found that the character-level system does not suffer from tokenization error and out-of- vocabulary issue. The JPO corpus contains many technical terms and loanwords like chemical com- pound names, which are more ... See full document
5
Active learning for interactive machine translation
... The incremental learning algorithm allows us to process each new training sample in constant time (i.e. the computational complexity of train- ing a new sample does not depend on the num- ber of previously seen ... See full document
10
Proceedings of the First Conference on Machine Translation: Volume 1, Research Papers
... The results of all shared tasks were announced at the conference, and these proceedings also include overview papers for the shared tasks, summarizing the results, as well as providing information about the data used and ... See full document
28
A Machine Translation System From Japanese Into English Based on Conceptual Structure
... A MACHINE TRANSLATION SYSTEM FROM JAPANESE INTO ENGLISH BASED ON CONCEPTUAL STRUCTURE A MACHINE TRANSLATION SYSTEM FROM JAPANESE INTO ENGLISH BASED ON CONCEPTUAL STRUCTURE Hiroshi Uchida and Kenji Sug[.] ... See full document
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