translation model domain adaptation

... clustered training data. 2 Domain Adaptation for Translation Models To motivate efforts in domain adaptation, let us review why additional training data can improve, but also decrease translation quality. Adding ... trans- lation models, which is only a subset of domain adaptation techniques in SMT. Mixture-modelling for language models is well established (Foster and Kuhn, 2007). Language model adaptation ... purpose as translation model adaptation, i.e. skewing the probability distribution in favour of in -domain translations. This means that LM adaptation may have similar effects as TM adaptation, ...

Ngày tải lên: 17/03/2014, 22:20

... the additional in -domain monolingual corpora to adapt the out-of -domain translation mod- el for domain- specific translation task. In detail, we build an adapted translation model in the following steps: • ... of further translation quality improve- ment. In this paper, we propose a novel adaptation method to adapt the translation model for domain- specific translation task by utilizing in -domain 459 Philipp ... sen- tences, and Wu et al. (2008) used an in -domain translation dictionary and monolingual corpora to adapt an out-of -domain translation model for the in- domain text. Differing from the above-mentioned...

Ngày tải lên: 19/02/2014, 19:20

... lexical weighting by domain. We induce unsupervised domains from large corpora, and we incorporate soft, probabilistic domain membership into a translation model. Unsupervised modeling of the training ... training 1 Language model adaptation is also prevalent but is not the focus of this work. 115 data come from; and even if we do, “subcorpus” may not be the most useful notion of domain for better translations. We ... Korea, 8-14 July 2012. c 2012 Association for Computational Linguistics Topic Models for Dynamic Translation Model Adaptation Vladimir Eidelman Computer Science and UMIACS University of Maryland College...

Ngày tải lên: 19/02/2014, 19:20

... the domain adaptation setting, by “bootstrapping” them based on known translations from the source domain. (3) Develop methods for integrating these mined dictio- naries into a phrase-based translation ... weights of a learned translation model to do well on a new domain. As expected, we shall see that unseen words pose a major challenge for adapting translation systems to distant domains. No machine ... of the translation error when mov- ing to new domains. Using an extension of a recent approach to mining translations from comparable corpora (Haghighi et al., 2008), we are able to find translations...

Ngày tải lên: 17/03/2014, 00:20

Ngày tải lên: 24/03/2014, 03:20

... do- main adaptation technique. Namely, we regard the pseudo-error corpus as the source domain and the real-error corpus as the target domain, and models are learnt that fit the target domain. In ... for the domain adaptation, which eliminates the need to change the learning algo- rithm. This method regards the models for the source domain as the prior distribution and learns the models for ... automatically. Fur- thermore, we apply domain adaptation, the pseudo-error sentences are from the source domain, and the real-error sentences are from the target domain. Experiments show that sta- ble...

Ngày tải lên: 19/02/2014, 19:20

... word-based translation model into a unified framework, called TransLM. The experiments show that this model gains better performance than both the language model and the word-based translation model. ... translation model. 3 Our Approach: Phrase-Based Translation Model for Question Retrieval 3.1 Phrase-Based Translation Model Phrase-based machine translation models (Koehn et al., 2003; D. Chiang, 2005; ... we propose a novel phrase-based translation model for question retrieval. Compared to the traditional word-based translation models, the phrase- based translation model is more effective be- cause...

Ngày tải lên: 20/02/2014, 04:20

... interpolation of several models, with weights tuned by MERT on the development set (Och, 2003). The baselines consisted of the lan- guage model, two phrase translation models, two lexical models, and a ... target-given-source phrase model 1 . 3 Exponential phrase models with shared features The model used in this work is based on the familiar equation for conditional exponential models: 1 To avoid confusion ... gen- eration and modeling of inflected forms un- observed in training data and decoding proce- dures for a model with non-local target-side feature dependencies. 1 Introduction Translation into...

Ngày tải lên: 07/03/2014, 22:20

... corpus depend on the domain from which the corpus is drawn. A change of predominant sense is often indicative of a change in domain, as different corpora drawn from different domains usually give ... 89–96, Sydney, July 2006. c 2006 Association for Computational Linguistics Estimating Class Priors in Domain Adaptation for Word Sense Disambiguation Yee Seng Chan and Hwee Tou Ng Department of Computer ... to these sense priors. The work of these researchers showed that when the domain of the training data differs from the domain of the data on which the system is applied, there will be a decrease...

Ngày tải lên: 08/03/2014, 02:21

... active learning for domain adaptation, fol- lowed by count-merging. Next, we describe an EM- based algorithm to estimate the sense priors in the new domain. Performance of domain adaptation us- ing ... to a new domain. Domain adaptation is necessary when the train- ing and target domains are different. In this paper, 49 did not deal with the porting of a WSD system to a different domain. Escudero ... (%) Percentage of adaptation examples added (%) a-c a r a-truePrior Figure 2: Adaptation process for all 21 nouns. of the BC training examples. At each adaptation iter- ation, WSJ adaptation examples...

Ngày tải lên: 08/03/2014, 02:21

... domains of discourse makes it an ideal candidate for domain adaptation. This work addressed two important questions of domain adaptation. First, we showed that for a given source and target domain, ... model, but all of these new techniques also make use of lexical features. Thus we believe that our adaptation methods could be also applied to those more refined models. While work on domain adaptation ... in -domain gold standard is 80.4%. We say that the adaptation loss for the baseline model is 7.6% and the adapta- tion loss for the SCL-MI model is 0.7%. The relative reduction in error due to adaptation...

Ngày tải lên: 08/03/2014, 02:21

... unintuitive word-for-word models; at the same time, seemingly capable models often have se- rious hidden problems — intuition is no substitute for experimentation. With translation ideas growing more ... visualize other syntax-based MT mod- els, other tree-to-tree or tree-to-string MT models, or models for paraphrasing. 2 Translation Framework It is useful at this point to give a brief descrip- tion ... new approaches to statistical ma- chine translation, and more ideas are being sug- gested all the time. However, it is difficult to deter- mine how well a model will actually perform. Ex- perienced...

Ngày tải lên: 08/03/2014, 04:22

... implement other translation models easily: 1) STSG-based model when 1d = ; 2) SCFG-based model when 1d = and 2h = ; 3) phrase-based translation model only (no reordering model) when 0c = ... We conducted Chinese-to-English translation ex- periments. We trained the translation model on the FBIS corpus (7.2M+9.2M words) and trained a 4- gram language model on the Xinhua portion of ... sequence alignment-based translation model. In this subsection, we first re- port the rule distributions and compare our model with the three baseline systems. Then we study the model s expressive...

Ngày tải lên: 17/03/2014, 02:20

... on feature-level multi-view adaptation. 3 Our Model Intuitively, source-specific and target-specific fea- tures can be drawn together by mining their co-occurrence with domain- independent (common) features, ... deemed as different domains. The task is defined as top category classifi- cation. For example, the dataset denoted as DA-EC consists of source domain: DA 1(+), EC 1(-); and target domain: DA 2(+), ... Co-Training for Domain Adaptation. In Pro- ceedings of NIPS, pages 1-9. Wenyuan Dai, Gui-Rong Xue, Qiang Yang and Yong Yu. 2007. Co-clustering Based Classification for Out- of -domain Documents....

Ngày tải lên: 23/03/2014, 14:20

... hi- erarchical rules simultaneously. 2 Proposed Model Given an original translation model, T M, our goal is to find the optimally reduced translation model, T M ∗ , which minimizes the degradation ... This restriction guarantees that the translational coverage of the reduced model is as high as those of the original translation model. In addition, our model does not prune the phrases and the ... sentence s, given the translation model T M. Consistency measures the similarity between the two groups of decoded target sentences produced by two different translation models. There are num- ber...

Ngày tải lên: 23/03/2014, 14:20

... and target models in both N-grams and ME models. It seems that with the adapted ME models, the same recognition accuracy for the tar- get evaluation data can be obtained with 50% less adaptation ... smaller, by penalizing weights with big absolute values. 3 Domain Adaptation of Maximum Entropy Models Recently, a hierarchical Bayesian adaptation method was proposed that can be applied to a large family ... the domain- specific model is applied. Intu- itively, this approach can be described as follows: the domain- specific parameters are largely deter- mined by global data, unless there is good domain- specific...

Ngày tải lên: 23/03/2014, 16:20

Ngày tải lên: 23/03/2014, 16:21

Ngày tải lên: 23/03/2014, 18:20

Ngày tải lên: 30/03/2014, 21:20

Ngày tải lên: 30/03/2014, 21:20