Machine Learning and Translation
Machine Learning for Hybrid Machine Translation
... hybrid machine translation (MT) that has been extended with machine learning components controlling its phrase ...“interesting” translation candidates from one or more ...
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Exploitation of Machine Learning Techniques in Modelling Phrase Movements for Machine Translation
... different machine learning techniques for distance phrase movements in machine ...structured learning, including maximum margin structure learning (MMS) and maximum margin regression ...
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A Machine Learning Method to Distinguish Machine Translation from Human Translation
... a machine learning ap- proach to distinguish machine translation texts from human texts in the sentence level au- ...a machine translation system looks like a real human ...
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A Machine Learning Approach to the Automatic Evaluation of Machine Translation
... a machine learning approach to evaluating the well- formedness of output of a machine translation system, using classifiers that learn to distinguish human reference translations from ...
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Automatic Translation of Biomedical Terms by Supervised Machine Learning
... possible translation relations— between terms in aligned corpora (Ahrenberg et ...the translation of a word in a text (relationship problem) whereas we are addressing the problem of producing the ...
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Prediction of Learning Curves in Machine Translation
... a Machine Learning context, Perlich et al. (2003) used learning curves for predicting maximum performance bounds of learning algorithms and to compare ...the learning curves of two ...
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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 ...
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Graph based Learning for Statistical Machine Translation
... a machine trans- lation perspective, we design and evaluate a global consistency model enforcing that similar inputs re- ceive similar ...a machine learning perspective, we apply graph-based ...
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Curriculum Learning for Domain Adaptation in Neural Machine Translation
... curriculum learning is ap- ...curriculum learning on new tasks; a potential direction for fu- ture work may be a curriculum that considers mul- tiple similarity scores ...
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Learning to Rank Algorithms and their Application in Machine Translation
... In the second task, we rerank an N-best list from a HPB system with 7491 features from a third party. The system uses six million parallel sentence pairs available to the DARPA BOLT Chinese-English task. This system ...
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An Interactive Machine Translation System with Online Learning
... State-of-the-art Machine Translation (MT) systems are still far from being ...chine Translation (IMT) framework, where the knowledge of a human translator is com- bined with the MT ...online ...
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Active Learning for Multilingual Statistical Machine Translation
... While we use consensus translations (He et al., 2008; Rosti et al., 2007; Matusov et al., 2006) as an effective method for co-training in this pa- per, unlike consensus for system combination, the source languages for ...
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Non linear Learning for Statistical Machine Translation
... statistical machine translation (SMT) systems usually use a linear com- bination of features to model the quality of each translation ...A learning framework is presented for training the ...
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Learning Deep Transformer Models for Machine Translation
... In our model, we use the dynamic linear combi- nation of layers for both encoder and decoder. For efficient computation, we only combine the out- put of a complete layer rather than a sub-layer. It should be noted that ...
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Semi Supervised Learning for Neural Machine Translation
... neural machine transla- tion (NMT) has made remarkable progress recently, NMT systems only rely on par- allel corpora for parameter ...target-to-source translation models serve as the encoder and decoder, ...
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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- ...
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Response based Learning for Grounded Machine Translation
... the translation and the original ...response-based learning over standard structured learning from reference ...response-based learning. Furthermore, translations produced by response- based ...
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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 ...
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Meta Learning for Low Resource Neural Machine Translation
... Sample Translations We present some sample translations from the tested models in Table 3. Inspecting these examples provides the insight into the proposed meta-learning algorithm. For in- stance, we observe that ...
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Transfer Learning for Low Resource Neural Machine Translation
... transfer learning and explains how we use it to im- prove machine translation ...the learning curves of transfer and no-transfer models, showing that transfer solves an overfitting problem, ...
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