[PDF] Top 20 Measuring Immediate Adaptation Performance for Neural Machine Translation
Has 10000 "Measuring Immediate Adaptation Performance for Neural Machine Translation" found on our website. Below are the top 20 most common "Measuring Immediate Adaptation Performance for Neural Machine Translation".
Measuring Immediate Adaptation Performance for Neural Machine Translation
... domain adaptation, in which a system learns from the correct output for each input immediately after making its predic- tion for that input, can dramatically improve system performance for interactive ... See full document
9
Overcoming Catastrophic Forgetting During Domain Adaptation of Neural Machine Translation
... general-domain performance close to the ini- tial general-domain model values during contin- ued training, while allowing parameters less im- portant to general-domain performance to adapt more aggressively ... See full document
7
Cost Weighting for Neural Machine Translation Domain Adaptation
... Data selection Some previous work (Luong and Manning, 2015; Sennrich et al., 2016b) has shown that the performance of NMT systems is highly sensitive to data size. Therefore, we follow the solution in (Luong and ... See full document
7
Unsupervised Domain Adaptation for Neural Machine Translation with Domain Aware Feature Embeddings
... of neural machine transla- tion models relies on the availability of high quality, in-domain ...Domain adaptation is required when domain-specific data is scarce or ...main adaptation ... See full document
6
Sentence Embedding for Neural Machine Translation Domain Adaptation
... for machine translation, only those that belong to the same or similar domains are typically able to improve translation ...Recently Neural Machine Translation (NMT) has become ... See full document
7
Incremental Domain Adaptation for Neural Machine Translation in Low Resource Settings
... the machine learning model under ...model performance while using the same amount of training ...domain adaptation in NMT in- clude query strategies that consider untranslated sentences as unlabeled ... See full document
10
Instance Weighting for Neural Machine Translation Domain Adaptation
... phrase-based machine translation domain ...to Neural Machine Translation (NMT) directly, because NMT is not a linear ...NMT performance by up to ... See full document
7
A Post editing Interface for Immediate Adaptation in Statistical Machine Translation
... proposed adaptation methods could lead to reduced techni- cal effort or translation ...As translation material we selected patents (W¨aschle and Riezler, 2012), where baseline translation ... See full document
5
Multi Domain Neural Machine Translation through Unsupervised Adaptation
... multi-domain translation scenarios call for infrastructures based on multi- ple specialised systems, each of which is tuned to maximise performance in a given ...however, translation requests rarely ... See full document
11
Curriculum Learning for Domain Adaptation in Neural Machine Translation
... the performance improvement of NMT ...good performance, and we do not need to use extra unlabeled-domain data to augment it any more, neither does curriculum ... See full document
13
Freezing Subnetworks to Analyze Domain Adaptation in Neural Machine Translation
... a neural machine translation system (the encoder, decoder, and each embedding space) and consider each component’s contri- bution to, and capacity for, domain ...on performance, and that ... See full document
9
Non Parametric Adaptation for Neural Machine Translation
... the performance of the various mem- ory ablations in Table ...in performance on all ...in performance (represented by ...to performance, by allowing the model to distinguish between relevant ... See full document
11
Regularized Training Objective for Continued Training for Domain Adaptation in Neural Machine Translation
... main adaptation scenario. Table 5 shows the re- sults of adaptation when only 2, 000 sentences of in-domain parallel text are ...improves performance by an addi- tional ... See full document
9
Simple, Scalable Adaptation for Neural Machine Translation
... by huge margins after the second stage of train- ing (adapter based refinement). Fine-tuning with adapters allows the model to see larger portions of the training data for high resource languages, and converges faster ... See full document
11
Domain Differential Adaptation for Neural Machine Translation
... domain adaptation strate- ...Differential Adaptation (DDA), where instead of smooth- ing over these differences we embrace them, directly modeling the difference between do- mains using models in a related ... See full document
11
Morphology aware Word Segmentation in Dialectal Arabic Adaptation of Neural Machine Translation
... in machine transla- tion in Section ...the neural machine translation approach that we use to train and adapt translation models for dialectal ... See full document
7
Cross Corpora Evaluation and Analysis of Grammatical Error Correction Models — Is Single Corpus Evaluation Enough?
... 2006). Machine translation approaches are being presently ap- plied for GEC (Junczys-Dowmunt et ...a translation problem from the erroneous text to the correct text (Mizumoto et ... See full document
6
Adaptation Data Selection using Neural Language Models: Experiments in Machine Translation
... domain adaptation in statistical ma- chine ...of neural language models for data ...in neural language models makes them more effective than n-grams for modeling un- known word contexts, which are ... See full document
6
Sentence Level Adaptation for Low Resource Neural Machine Translation
... Li et al. (2016) present a dynamic NMT ap- proach where the general NMT model is adapted per-sentence; however, they adapt on only a single similar sentence and employ their system in a high- resource context. We propose ... See full document
9
Domain Adaptation and Attention Based Unknown Word Replacement in Chinese to Japanese Neural Machine Translation
... domain adaptation method to disambiguate the meaning of a word according to its ...domain adaptation method, but by adding large monolingual data to make the language modeling more ... See full document
9
Related subjects