in-domain language models
The Karlsruhe Institute of Technology Translation Systems for the WMT 2012
... tional language models boosted the system quality: around ...three language models were log-linearly combined: In addition to the afore- mentioned, two additional language models ...
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Domain Specific Language Testing Framework
... of domain-specific models and languages is ...the domain-specific language to be expression ...the domain elements have to be transformable to the generic metamodel elements so their ...
131
Context Adaptation in Statistical Machine Translation Using Models with Exponentially Decaying Cache
... of language and translation models to a new domain using the cache-based mixture models as described ...cache models on or off using additional command-line arguments when running Moses ...
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NUS at WMT09: Domain Adaptation Experiments for English Spanish Machine Translation of News Commentary Text
... on domain adaptation, combining a small in-domain News Com- mentary bi-text and a large out-of-domain one from the Europarl corpus, from which we built and combined two separate phrase ...two ...
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Improving Multi label Emotion Classification by Integrating both General and Domain specific Knowledge
... general language mod- els have achieved state-of-the-art results in many popular tasks such as sentiment analy- sis and QA ...characteristics. Domain knowledge should be helpful in do- main relevant ...
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Hierarchical Latent Words Language Models for Robust Modeling to Out Of Domain Tasks
... Our basic assumption is domain-matched train- ing data is not available. Thus, for LM train- ing, we used the Corpus of Spontaneous Japanese (CSJ) whose domain is a spontaneous lecture task (Maekawa et al., ...
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Development of physical security protection metamodel
... to domain user. Domain model developers will normally need to spend a lot of times in understanding the nature of the domain which they de sire to ...purpose language such as the Unified ...
25
The AFRL MITLL WMT15 System: There’s More than One Way to Decode It!
... (factored) language models; one using 600 classes on the in-domain target-side parallel data, and the other using the LDC Gigaword-English v5 NYT ...
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Balancing data driven and rule based approaches in the context of a Multimodal Conversational System
... building language models is to “migrate” a corpus of a different domain to the MATCH ...MATCH domain. The identification of the linguistic units in the out-of-domain corpus is done ...
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Cross Domain NER using Cross Domain Language Modeling
... target domain. Yang et al. (2017) jointly train source- and target-domain models with shared pa- rameters, Lin and Lu (2018) add adaptation layers on top of existing ...cross- domain NER data ...
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Sieg at MEDIQA 2019: Multi task Neural Ensemble for Biomedical Inference and Entailment
... natural language inference (NLI) and question entailment (RQE) in the biomed- ical ...final models for the NLI and RQE tasks achieve the 4 th and 2 nd rank on ...
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Domain Adaptation from User level Facebook Models to County level Twitter Predictions
... As the first step, we adjust the Twitter county-level word frequencies to help mitigate the influence of spatial variations and confounds in word use. This is done by identifying outlier feature values for a given ...
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Effective Selection of Translation Model Training Data
... However, domain-specific machine translation has few parallel corpora for translation model training in the domain of inter- ...expand domain-specific sen- tence pairs from large scale ...
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An Empirical Investigation of Discounting in Cross Domain Language Models
... Divergent corpora In addition to these two cor- pora, which were produced from a single contigu- ous batch of documents, we consider testing on cor- pus pairs with varying degrees of domain difference. We ...
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Models, Theories, and Language
... The first requirement, according to which the interpretation of a theory relies on a medium of abstract objects, presupposes a top-down account of meaning. The semantic view is not a bottom-up account, according to ...
22
Domain Adaptation of Maximum Entropy Language Models
... -gram models which are typically used in speech ...ME models requires even more memory than training simple ME mod- els, proportional to the number of nodes in the hi- ...and domain-specific priors. ...
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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 into ...
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A General Technique to Train Language Models on Language Models
... Training is often done on the basis of a corpus of actual language use in a certain domain. If each sentence in this corpus is annotated by a list of transitions of an FA recognizing the sentence or a parse ...
14
Language Models for Machine Translation: Original vs Translated Texts
... English-original language model and translations produced with a LM created from French-translated-to-English texts, we conducted a human evaluation campaign, using Amazon’s Mechanical Turk as an inexpensive, ...
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Synchronous Models of Language
... Informally speaking, during a SynchUVG-DL derivation, the two synchronous productions in a pair of synchronized vectors must be applied at the same time and must rewrite linked occurrenc[r] ...
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