... French ones, to a sink, to control the flow quantity we want to go through the words. 2.1 Flow networks We meet here the notion of flow networks that we can formalise in the following way (we ... reader to (Ford and Fulkerson, 1962; Klein, 1967). 2.2 Alignmentmodels Flows and networks define a general framework in which it is possible to model alignments be- tween words, and to ... translations for the English term. 4 Conclusion We presented a new model forwordalignment based on flow networks. This model allows us to integrate different types of constraints in the search for...
... Retrieving Word AlignmentsTwo word- alignment retrieval schemes are de-signed for BiTAMs: the uni-direction alignment (UDA) and the bi-direction alignment (BDA). Bothuse the posterior mean of the alignment ... Null word and Laplace smoothing for the BiTAM models. We train, for comparison, IBM-1&4 and HMM models with 8 iterations of IBM-1, 7 for HMMand 3 for IBM-4 (18h743) with Null word ... Incorporation of Word “Null”Similar to IBM models, “Null” word is used for the source words which have no translation coun-terparts in the target language. For example, Chi-nese words “de” ()...
... areless than 20 percent.2 1 : n Word Alignment Our discussion of uni-directional alignments of word alignment is limited to IBM Model 4.Definition 1 (Word alignment task) Let eibethe i-th ... two word alignmentsas an alignment point, 2) add new alignment pointsthat exist in the union with the constraint that anew alignment point connects at least one previ-ously unaligned word, ... purpose ofthe wordalignment task is to obtain a lexicaltranslation probability p(¯fi|¯ei), which is a 1 : nuni-directional word alignment. The initial ideaunderlying the IBM Models, consisting...
... bilin-gual wordalignment finds word- to -word connec-tions across languages. Originally introduced as abyproduct of training statistical translation models in (Brown et al., 1993), wordalignment ... Log-linear modelsfor word alignment. In Meeting of the Association for Computa-tional Linguistics, pages 459–466, Ann Arbor, USA.I. D. Melamed. 2000. Models of translational equivalenceamong words. ... new information resulting in im-proved alignments.2 Constrained Alignment Let an alignment be the complete structure thatconnects two parallel sentences, and a link beone of the word- to-word...
... words to the right and left of the verb, identified using POS tags, represented by has_narrow(snt, word_ position, word) : has_narrow(snt1, 1st _word_ left, mind). has_narrow(snt1, 1st _word_ right, ... the positions of the words, represented by has_narrow_trns(snt, word_ position, portuguese _word) : has_narrow_trns(snt1, 1st _word_ right, como). has_narrow_trns(snt1, 2nd _word_ right, um). … ... for the disambigua-tion of verbs. We plan to further evaluate our approach for other sets of words, including other parts-of-speech to allow further comparisons with other approach-es. For...
... Automatically-extracted thesauri for cross-language IR: When better is worse. In Proceed-ings of COMPUTERM’98.Eric Gaussier. 1998. Flownetworkmodelsfor word alignment and terminology extraction ... language word. is expressed as follows: a word qualifies for clus-tering ifAs before, are all the target language wordsthat cooccur with source language word .Similarly to the most frequent words, ... clustering. Those wordsthat are considered for clustering should account for more than of the cooccur-rences of the source language word with any tar-get language word. If a word falls below...
... short words.340Combining Clues forWord Alignment Rirg TiedemannDepartment of LinguisticsUppsala UniversityBox 527SE-751 20 Uppsala, Swedenjoerg@stp.ling.uu.seAbstractIn this paper, a word ... bilinguallexical information. Wordalignment approachesfocus on the automatic identification of translationrelations in translated texts. Alignments are usu-ally represented as a set of links between wordsand ... an alignment clue for the cor-responding word pairs. The likelihood of eachtranslation alternative can be weighted, e.g., byfrequency (if available).2.3 Clue CombinationsSo far, word alignment...
... based on word alignment. In this paper we introduce a confidence mea-sure forword alignment, which is robust to extraor missing words in the bilingual sentence pairs,as well as wordalignment ... confidence sentencealignments and alignment links from mul-tiple word alignments of the same sen-tence pair. Additionally, we removelow confidence alignment links from the word alignment of a bilingual ... the same word does in-crease the confusion forwordalignment and re-duce the link confidence. On the other hand, ad-ditional information (such as the distance of the word pair, the alignment...
... two parameters for the dis-tortion probability: one for head words and the other for non-head words. Distortion Probability for Head Words The distortion probability for head words represents ... two wordalignmentmodelsfor language pairs L1-L3 and L2-L3, respectively. And then, with L3 as a pivot language, we can build a word alignment model for L1 and L2 based on the above two models. ... language word similarity of the Chinese word c and the Japanese word given the English word );,( efcsimfeFigure 1. Similarity Calculation English word e. For the ambiguous English word e,...
... as 1.In building wordalignment models, a special“NULL” word is usually introduced to address tar-get words that align to no source words. Since thisphysically non-existing word is not in the ... computational42 Constrained WordAlignment Models The framework that we propose to incorporate sta-tistical constraints into wordalignmentmodels isgeneric. It can be applied to complicated models such IBM ... candidate. This information is de-rived before wordalignment model training and willact as soft constraints that need to be respected dur-ing training and alignments. For a given word pair,the...
... withall word space models, which facilitates word space based applications.The package is written in Java and defines astandardized Java interface forword space algo-rithms. While other word ... July 2010.c2010 Association for Computational LinguisticsThe S-Space Package: An Open Source Package forWord Space Models David JurgensUniversity of California, Los Angeles,4732 Boelter ... algorithms,code documentation and mailing list archives.2 Word Space Models Word space models are based on the contextualdistribution in which a word occurs. This ap-proach has a long history in linguistics,...
... rea-sonable alignments, wordalignmentmodels mustconstrain the set of alignments considered. In thissection, we discuss and compare alignment fami-lies used to train our discriminative models. Initially, ... many-to-one block alignment potential, and efficient pruning, ITG models canyield state-of-the art word alignments, even whenthe underlying gold alignments are highly non-ITG. Our models yielded ... across alignments. Specif-ically, for each alignment cell (i, j) which is nota possible alignment in a∗, we incur a loss of 1when aij= a∗ij; note that if (i, j) is a possible alignment, ...
... syntax-based translation framework.Most wordalignmentmodels distinguish trans-lation direction in deriving wordalignment matrix.Given a parallel sentence, word alignments in twodirections are ... different word align-ment combination methods4 ConclusionsWe presented a simple yet effective method for wordalignment symmetrization and combinationin general. The problem is formulated ... DARPATransTac program for funding and the anonymousreviewers for their constructive suggestions.ReferencesN. F. Ayan. 2005. Combining Linguistic and Machine Learn-ing Techniques forWordAlignment Improvement....
... model for Chinese word segmentation was pro-posed. Gao et al. (2005) further developed it to a linear mixture model. In these statistical models, language models are essential forword segmen-tation ... bigram probability Pm(wy|wx) for seen bigram wxwy in training corpus, unigram probability Pm(w) and backoff coefficient αm(w) for any word w. For any wx and wy in the vocabulary, ... pages 1001–1008,Sydney, July 2006.c2006 Association for Computational LinguisticsDiscriminative Pruning of Language Modelsfor Chinese Word Segmentation Jianfeng Li Haifeng Wang Dengjun...