[PDF] Top 20 Fast Domain Adaptation of SMT models without in Domain Parallel Data
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Fast Domain Adaptation of SMT models without in Domain Parallel Data
... a SMT system tailored to a customer’s domain, a sample dataset is ...pilot SMT system leveraging only sample mono-lingual source corpus, and previously trained library of ...in-domain ... See full document
10
Analysing the Effect of Out of Domain Data on SMT Systems
... what domain actually is, and why it ...test data domains reduces translation performance has been observed in previous studies, and will be confirmed here for multiple data sets and languages, but ... See full document
11
Domain Adaptation for Statistical Machine Translation with Monolingual Resources
... translation models are retrained on the extracted ...cross-domain adaptation, in which a small sample of parallel in-domain text is as- sumed, and dynamic adaptation, in which ... See full document
8
Adaptation Data Selection using Neural Language Models: Experiments in Machine Translation
... to domain adaptation in statistical ma- chine ...guage models trained on small in-domain text to select similar sentences from large general-domain corpora, which are then incorporated ... See full document
6
Latent Domain Phrase based Models for Adaptation
... in-domain data has a different but complementary goal to another line of research aiming at combining a domain- adapted system with the another trained on the in- domain data (Koehn and ... See full document
11
Translation Model Interpolation for Domain Adaptation in TectoMT
... implement domain adaptation by TM interpolation in the TectoMT sys- tem, a hybrid SMT system based on deep language processing and deep ...(IT) domain, with only 1000 in-domain ... See full document
8
Domain Adaptation via Pseudo In Domain Data Selection
... efficient domain adaptation for the task of statistical machine translation based on extracting sentences from a large general- domain parallel corpus that are most relevant to the target ... See full document
8
Fast Easy Unsupervised Domain Adaptation with Marginalized Structured Dropout
... Unsupervised domain adaptation often re- lies on transforming the instance represen- ...bag-of-words models, and ignore the structured features present in many problems in ... See full document
7
Fast Domain Adaptation of Semantic Parsers via Paraphrase Attention
... sequence-to-sequence/tree models were proposed (Jia and Liang, 2016; Dong and Lapata, ...crafted domain specific gram- mar/lexicon, thereby improving ... See full document
10
Edit Distance: A New Data Selection Criterion for Domain Adaptation in SMT
... other data selection criterion is a perplexity-based model which can be found in the field of language ...for SMT adaptation and showed that the fast and simple technique allows to discard ... See full document
6
Structured and Unstructured Cache Models for SMT Domain Adaptation
... topic models which learn aligned topics directly from parallel or comparable corpora (Zhao and Xing, 2006; Boyd-Graber and Blei, 2009; Jagar- lamudi and Daum´e III, ... See full document
9
Multi Domain Adaptation for SMT Using Multi Task Learning
... specific domain using a gen- eral model that is trained over a hotchpotch of bilin- gual ...Therefore, domain adaptation is cru- cial for SMT systems to achieve better ...on domain ... See full document
11
Building Domain Specific Taggers without Annotated (Domain) Data
... We next present some examples that illustrate strengths and weaknesses of the current model. An example that shows that EM training makes good adjustment to the domain is the improvement in tagging of verbal ... See full document
9
Exploring Options for Fast Domain Adaptation of Dependency Parsers
... target domain texts may be available that can be leveraged in this or that way to facilitate domain ...of domain adaption, previous work focused on weakly supervised methods to re-train parsers on ... See full document
12
Fast Domain Adaptation for Part of Speech Tagging for Dialogues
... on domain adaptation has focused on parsing rather than on POS tagging ...perform domain adaptation for a de- pendency ...unannotated data to inform the training of another tagger in a ... See full document
8
Effective Selection of Translation Model Training Data
... for data selection rather than the conventional n-gram language ...in data selection (Duh et ...language models to score the sentence pairs are ... See full document
5
Domain Adaptation for Authorship Attribution: Improved Structural Correspondence Learning
... 3.2 Pivot Features for Authorship Attribution The SCL algorithm depends heavily on the pivot features being domain-independent features, and as discussed in Section 2, which features make sense as pivot features ... See full document
10
Domain Adaptation of Maximum Entropy Language Models
... Bayesian adaptation method is a generalization of the three approaches de- scribed ...and domain-specific parameters, using parameters built from pooled data as priors for domain-specific ... See full document
6
Empirical Study of Unsupervised Chinese Word Segmentation Methods for SMT on Large scale Corpora
... The computational complexity of our method is linear in the number of iterations, the size of the corpus, and the complexity of calculating the ex- pectations on each sentence or sentence pair. In practical applications, ... See full document
7
FLORS: Fast and Simple Domain Adaptation for Part of Speech Tagging
... Our FLORS tagger provides best ALL accuracies in all domains but WSJ, where C&W has best re- sults. The good performance of C&W is rather un- surprising since the embeddings were created for the 130,000 most ... See full document
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