[PDF] Top 20 Learning from Chunk based Feedback in Neural Machine Translation
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Learning from Chunk based Feedback in Neural Machine Translation
... Likert scale. The main problem of such methods is that users are not qualified enough to provide re- liable feedback for the whole sentence. Since dif- ferent users do not adhere to a single set of guide- lines, ... See full document
6
Neural Machine Translation with Adequacy-Oriented Learning
... Although Neural Machine Translation (NMT) models have advanced state-of-the-art performance in machine translation, they face problems like the inadequate ...real translation ... See full document
8
Active Learning for Interactive Neural Machine Translation of Data Streams
... active learning techniques to the translation of unbounded data streams via interactive neural machine ...select, from an unbounded stream of source sentences, those worth to be ... See full document
10
Semi Supervised Learning for Neural Machine Translation
... In this paper, we propose semi-supervised learning for neural machine translation. Given la- beled (i.e., parallel corpora) and unlabeled (i.e., monolingual corpora) data, our approach jointly ... See full document
10
Learning to Actively Learn Neural Machine Translation
... in neural machine translation systems, previous work have consid- ered training a seperate language model on the tar- get side (Jean et ...back translation approaches (Sennrich et ...improve ... See full document
11
Reinforcement Learning for Bandit Neural Machine Translation with Simulated Human Feedback
... Machine translation is a natural candidate problem for reinforcement learning from human feedback: users provide quick, dirty ratings on candidate translations to guide a system to ... See full document
11
Multi agent Learning for Neural Machine Translation
... Conventional Neural Machine Translation (NMT) models benefit from the training with an additional agent, ...dual learning, and bidirectional decoding with one agent decod- ing ... See full document
10
A Study of Reinforcement Learning for Neural Machine Translation
... t learning (RL) is an effective approach for improving the performance of neural machine translation (NMT) ...large-scale translation tasks as testbeds, we conduct a sys- tematic study ... See full document
10
Reinforcement Learning based Curriculum Optimization for Neural Machine Translation
... Following Wang et al. (2018), we use the Paracrawl and WMT English-French corpora for our experiments. These contain 290M and 36M training sentences respectively. WMT is relatively clean, while a large majority of ... See full document
8
Competence based Curriculum Learning for Neural Machine Translation
... riculum learning for NMT, although other related works have met with mixed ...a translation system for a sin- gle epoch, presenting the training examples in an easy-to-hard order based on sentence ... See full document
11
Character based Neural Machine Translation
... Character-based Machine Translation Word embeddings have been shown to boost the performance in many NLP tasks, including ma- chine ...lookup- based embeddings are limited to a finite-size vo- ... See full document
5
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 ... See full document
6
Proceedings of the 3rd Workshop on Neural Generation and Translation
... Machine Translation of Restaurant Reviews: New Corpus for Domain Adaptation and Robustness Alexandre Berard, Ioan Calapodescu, Marc Dymetman, Claude Roux, Jean-Luc Meunier and Vas- silina Nikoulina ... See full document
16
Chunk based Decoder for Neural Machine Translation
... as machine translation (Luong and Manning, 2016), document modeling (Li et ...of learning syntactic structures of target ...the chunk-word level to explicitly capture the syntactic structure ... See full document
12
Can Neural Machine Translation be Improved with User Feedback?
... In our experiments, learning from feedback starts from a pre-trained English to Spanish NMT model that has not seen in-domain data (i.e., no product title translations). The NMT base- line ... See full document
14
Chunk Based Bi Scale Decoder for Neural Machine Translation
... a chunk-based bi-scale decoder for neural machine translation, in which way, the target sentence is translated hierarchically from chunks to words, with information in different ... See full document
7
Tutorial: De mystifying Neural MT
... Neural Statistical Machine Translation Neural Machine Translation Encoder Decoder Sequence-to-sequence learning: Encoder Sequence-to-sequence learning: Decoder Let’s use a simple NN for [r] ... See full document
84
NICT’s participation to WAT 2019: Multilingualism and Multi step Fine Tuning for Low Resource NMT
... Tamil→English translation we obtained a BLEU score of ...comes from the strengthened encoder which is pretrained on the English–Hindi ...transfer learning by ... See full document
5
Alignment Based Neural Machine Translation
... the translation probability depending on an intermediate compu- tation of an alignment ...model from the lexical model has its own advantages: First, this leads to more flexi- bility in modeling and ... See full document
12
Graph Based Translation Memory for Neural Machine Translation
... subsets based on the averaged similarity of each sentence in the retrieved trans- lation ...memory. From the results reported in Table 4, it is observed that the proposed G-TFM outperforms the base- line TF ... See full document
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