... quantization errorwould be approximately 0.5. We also try setting δby optimization on held-out data.4 Evaluation and ConclusionsWe trained and measured the perplexity of 4-gram language models ... m-gram language mod-eling. In Proceedings of ICASSP-95, vol. 1,181–184.Koehn, Philipp, and Christof Monz. 2006. Manualand automatic evaluation of machine translation between European languages. ... recognition and machine translation. De-spite the criticism that they ignore the structure ofnatural language, simple N-gram models, whichestimate the probability of each word in a textstring based...
... evaluated them on a numberof classification tasks related to incremental dependency parsing. These tasks were con-ventional multiclass classification, hiearchi-cal classification, and a structured ... June 2007.c2007 Association for Computational LinguisticsLogistic Online Learning Methods and Their Application to Incremental Dependency Parsing Richard JohanssonDepartment of Computer ScienceLund ... Oronoz. 2003. Constructionof a Basque dependency treebank. I n Proceedings ofthe TLT, pages 201–204.Sabine Buchholz and Erwin Marsi. 2006. CoNLL-Xshared task on multilingual dependency parsing. ...
... presenting two clustering -based al-gorithms. The first algorithm deals with only onecontext. It is basedon comparing two context sets:one is related to the expression and the other is se-mantically ... approach is also based on the idea of the relatedness between the expres-sion and the surrounding context. Unlike the men-tioned study, we do not focus our attention only on idioms. So far ... examineone of such problems, the problem of automaticfigurative language use detection. We propose aframework for figurative language detection based on the idea of sense differentiation. Then,...
... sentences, and (3) robust translation of erroneous speech recognition results. 1 Introduction A spoken- languagetranslation system requires the ability to treat long or ill-formed input. An ... any translation result. This paper proposes an input-splitting method for robust spoken- language translation. The proposed method splits input into well- balanced translation units basedon ... results using semantic distance calculation, and its application to speech translation. In Proc. of ACL//EACL Workshop onSpoken Language Translation, pages 24-31. 427 to the right-neighboring...
... increase in entropy. 5 Conclusions In this paper, we presented a language model based on a kind of simple dependency gram- mar. The grammar consists of head-dependent relations between words and ... reestimation algorithm iteratively until it converges to an op- timal dependency grammar. On the average, 26 iterations were done for the training sets. Smoothing is needed for language modeling ... frequency of each dependency relation is cal- culated. Basedon the frequencies, probabili- ties of dependency relations are recalculated by C(wp + w~) The process w,) = C(w continues until...
... aslexical selection accuracy and BLEU score.1 IntroductionRecent approaches to statistical speech translation have relied on improving translation quality withthe use of phrase translation (Och and ... role of context char-acterized through dialog acts (DAs) in statis-tical translation. We demonstrate the integra-tion of the dialog acts in a phrase -based statis-tical translation framework, ... typicallynoisy translations.6 Discussion and Future WorkIt is important to note that the dialog act tags usedin our translation system are predictions from themaxent based DA tagger described in Section...
... proportion of words appearingonly once among the unique words; this gives anindication of the proportion of words that occurrarely. We see that the asymptotic behaviour de-pends on d but not on ... among rare words, with thecontribution of more common words being neg-ligible. HPYLM performs worse than MKN on words that occurred only once (on average) andbetter on other words, while HPYCV ... a variety of linguistic applications, in-cluding speech recognition, handwriting recogni-tion, optical character recognition, and machine translation. Most language models fall into theclass...
... of the conventionalmethod.In this section, we first discuss the effect of ourmethod onparsing accuracy, separately for bun-Table 6: Comparison of parsing accuracy betweenconventional method ... important to con-sider the features. Although there have beenvery few studies onparsing monologue sentences,some studies onparsing written language havedealt with long-sentence parsing. To ... are considered as suitable language units for simplicity. To evaluate the effectivenessof our method for Japanese spoken monologue, weconducted an experiment ondependency parsing of the spoken...
... summarization methods can be gener-ally categorized into extraction -based methods and abstraction -based methods. In this paper, we focus on extraction -based methods. Extraction- based summarization ... machine translation quality prediction and cross -language summarization, respectively. We discuss in Section 6 and conclude this paper in Section 7. 2 Related Work 2.1 Machine Translation Quality ... Association for Computational Linguistics, pages 917–926,Uppsala, Sweden, 11-16 July 2010.c2010 Association for Computational LinguisticsCross -Language Document Summarization Basedon Machine Translation...
... the transition -based category is thatthey all need a classifier to perform classificationconditioned on a certain configuration. However,they differ from each other in the classification re-sults. ... word-pair classification model for dependency parsing (section 2) and the generation methodof projected classification instances (section 3).Then we describe an application of the projectedparser: ... parser (section 4). After the comparisonswith previous works ondependencyparsing andprojection, we finally five the experimental results.2 Word-Pair Classification Model2.1 Model DefinitionFollowing...