... models into low-frequency word pairs in bilingual sentences, and then improved the word alignment performance. The SRH regardsall of the different words coupled with the same word in the synonym pairs ... sen-140Figure 1: Graphical model of HM-BiTAM alignment quality.2 Bilingual WordAlignment ModelIn this section, we review a conventional gener-ative wordalignment model, HM-BiTAM (Zhaoand Xing, ... (fjn|En, ajn, zn; B ): sample atarget word fjngiven an aligned source word and topicwhere alignment ajn= i denotes source word eiand target word fjnare aligned. α is a parame-ter...
... translationsby wordalignment but also becaus e of such interfaceissues that aligning words manually has the reputa-tion of being a very tedious task.3 YawatYawat (Yet Another WordAlignment Tool) ... Ex-plorer.Figure 3: Alignment v isualization with Yawat. As the mouse is moved over a word, th e word and all words linkedwith it are highlighted. The highlighting is removed when the mouse leaves the word ... the term wordalignment 1Yawat was first presented at the 2007 Linguistic Annota-tion Workshop (Germann, 2007).to refer to any form of alignment that identifies wordsor groups of words as...
... improvements on word alignments(Ayan et al., 2005; Moore, 2005; Ittycheriah andRoukos, 2005; Taskar et al., 2005).The standard technique for evaluating word alignments is to represent alignments ... algorithms to generate word alignments. However, evaluating word alignmentsis difficult because even humans have difficultyperforming this task.The state-of-the art evaluation metric— alignment error ... pairs of words) and to compare the gen-erated alignment against manual alignment of thesame data at the level of links. Manual align-ments are represented by two sets: Probable (P )alignments...
... model many-to-one word alignments,where each source word is aligned with zero orone target words, and therefore each target word can be aligned with many source words. Eachsource word is labelled ... one-to-many alignments, where each target word is aligned with zero or more source words.Many-to-many alignments are recoverable usingthe standard techniques for superimposing pre-dicted alignments ... null, denot-ing no alignment. An example word alignment is shown in Figure 1, where the hollow squaresand circles indicate the correct alignments. In thisexample the French words une and autre...
... automatic word alignment. Context vec-tors are built from the alignments found in a paral-lel corpus. Each aligned word type is a feature inthe vector of the target word under consideration.The alignment ... for the automatic word alignment described below.5.2.2 Alignment ContextContext vectors are populated with the links towords in other languages extracted from automatic word alignment. We applied ... the target word P(W) is the probability of seeing the word P(f) is the probability of seeing the featureP(W,f) is the probability of seeing the word and the featuretogether.3.3 Word Alignment The...
... 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, ... context word . ijctje 0=ijct if does not occur in Set i . je(4) Given the English word e, calculate the cross-language word similarity between the Chinese word and the Japanese word ... one for head words and the other for non-head words. Distortion Probability for Head Words The distortion probability for head words represents the relative position of the head word of the...
... 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 ... am1specifies the indices of source wordsthat target words are aligned to.In an HMM-based wordalignment model, sourcewords are treated as Markov states while targetwords are observations that are ... generative word alignment models. Prior knowledge serves as softconstraints that shall be placed on translation lexi-con to guide wordalignment model training and dis-ambiguation during Viterbi alignment...
... a family of word alignment. Definition 1. The ITG alignment family is a set of word alignments that has at least one BTG deriva-tion.ITG alignment family is only a subset of word alignments because ... am-biguity in wordalignment is the case where two ormore derivations d1, d2, dkof G have the sameunderlying wordalignment A. A grammar G is non-spurious if for any given word alignment, ... Null -word Attachment AmbiguityDefinition 4. For any given sentence pair (e, f) andits alignment A, let (e, f) be the sentence pairswith all null-aligned words removed from (e, f).The alignment...
... 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, ... mechanism to aug-ment one source word into several source wordsor delete a source word, while a NULL insertionis a mechanism of generating several words fromblank words. Fertility uses a conditional...
... sums, for each word w, the number of wordsnot linked to w that fall between the first and lastwords linked to w. The other features counts onlysuch words that are linked to some word other thanw. ... havea function word not linked to anything, betweentwo words linked to the same word. exact match feature We have a feature thatsums the number of words linked to identicalwords. This is motivated ... association with respect to a word in asentence pair to be the number of association types (word- type to word- type) for that word that havehigher association scores, such that words of bothtypes occur...
... bilin-gual wordalignment finds word- to -word connec-tions across languages. Originally introduced as abyproduct of training statistical translation modelsin (Brown et al., 1993), wordalignment ... 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 connections that makeup an alignment. ... traditional wordalignment techniques.Otherwise, the features remain the same,including distance features that measureabsj|E|−k|F |; orthographic features; word frequencies; common-word...
... methods for word alignment. In addition, we improve the word alignment results by combining the results of the two semi-supervised boost-ing methods. Experimental results on word alignment ... Statisti-cal Word Alignment. In Proc. of the 10th Machine Translation Summit, pages 313-320. Hua Wu, Haifeng Wang, and Zhanyi Liu. 2005. Alignment Model Adaptation for Domain-Specific Word Alignment. ... train the alignment models with unlabeled data. A question about wordalignment is whether we can further improve the performances of the word aligners with available data and available alignment...
... VBNNNSDTAUXThejobsarecareeroriented.lesemploissontaxéssurlacarrière..LegendCorrect proposed wordalignment consistent with human annotation.Proposed wordalignment error inconsistent with human annotation. Word alignment constellation that renders ... word alignment. This dependenceruns deep; for example, Galley et al. (2006) requires word alignments to project trees from the target lan-guage to the source, while Chiang (2005) requiresalignments ... compat-ibility with the word alignment. For a constituent cof t, we consider the set of source words scthat arealigned to c. If none of the source words in the lin-ear closure s∗c(the words between...
... 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, ... contain one word. Then the similarity score of themerged cluster will be the similarity score ofthe word pair.2. Merge a cluster that contains a single word and a cluster that contains wordsand ... the -word cluster, av-eraged with the similarity scores between thesingle word and all words in the cluster. Thismeans that the algorithm computes the similar-ity score between the single word...
... optimal alignment. Section 2 describes the clue alignment modeland ways of estimating parameters from associ-ation scores. Section 3 introduces the alignment approach which is based on wordalignment ... therefore,they can be dismissed in the alignment process.3 Clue Alignment Word alignment clues as described above can beused to model the relations between words oftranslated texts. Parameters ... information. Wordalignment approachesfocus on the automatic identification of translationrelations in translated texts. Alignments are usu-ally represented as a set of links between wordsand...