... order model is taken to be the word frequenciesin the Web 1T corpus. The Brown corpus was re-tokenized to match the tokenization style of the Web1T dataset resulting in 1, 186,262 tokens in 52 ,10 8sentences. ... 52 ,10 8sentences. The Web 1T dataset has a 13 million word vocabulary consisting of words that appear 10 0times or more in its corpus. 769 sentences in Brownthat contained words outside this vocabulary ... and Linda C. Bauman Peto. 19 95. Ahierarchical Dirichlet language model. Natural Lan-guage Engineering, 1( 3) :1 19 .Y.W. Teh. 2006. A hierarchical Bayesian language model based on Pitman-Yor...
... the term wordalignment 1 Yawat 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 ... sub-sentential alignments of paral-lel text.” Linguistic Annotation Workshop (LAW’07), 12 1 12 4. Prague, Czech Republic.Hwa, Rebecca and Nitin Madnani. 2004.“The umiacs wordalignment interface.”http://www.umiacs.umd.edu/∼nmadnani/ alignment/ forclip.htm.Lambert, ... 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)...
... usually 2, i.e. bigram model (Lin and Tsai, 19 87; Gu et al., 19 91; Fu et al., 19 96; Ho et al., 19 97; Sproat, 19 90; Gao et al., 2002; Lee 2003). From the studies (Hsu 19 94; Tsai and Hsu, 2002; ... 量刑/事實 /1, 關於/兩性 /1, 關與/實施 /1, 生殖/實施 /1, 關於/事實 /1, 關於/史實 /1 WSM Set 關於(guan yu)/7, 實施(shi shi)/4, 兩性(liang xing)/3, 量刑(liang xing)/2, 知識(zhi shi)/2, 事實(shi shi)/2, 失事(shi shi) /1, 關與(guan yu) /1, ... are (18 .9%, 10 .1% ) and (25.6%, 16 .6%), respectively. From Table 3b, the tonal and toneless STW improvements of the BiGram by using the WP identifier and the WSM are (8.6%, 11 .9%) and (17 .1% ,...
... from the Europarl corpus4 #word- transl. pairs #word- transl. pairsDA 10 4K FR 90KDE 13 3K IT 96KEL 60K PT 86KEN 11 9K SV 97KES 11 9K ALL 994KFI 89KTable 3: Number of word- translation pairs for ... 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 ... introduced above.For the word alignment, we apply standard tech-niques derived from statistical machine transla-tion using the well-known IBMalignment mod-els (Brown et al., 19 93) implemented in...
... ∑Δ=−Δ=−−−−−−−−−=−−=ΔΔ'':,':, 1& apos;1EJ 1& apos;1EJEJ 1& apos ;1& apos; 11 ),'|,(Pr)'|(Pr)'|(Prjjjjjjiiiiiiiijjjjjj⊙⊙⊙⊙⊙⊙⊙⊙ (12 )The English word in position is aligned to the Japanese word ... build a word alignment model for L1 and L2 based on the above two models. Here, we call this model an induced model. With this induced model, we per-form wordalignment between languages L1 and ... given English word using all other words as context in Set 1 and Set 2, respectively. CEVEJV>=< ),(, ),,(),,( 11 2 211 1CE nnctectecteV >=< ),(, ),,(),,(2222 211 EJ nnctectecteV...
... Constrained WordAlignment ModelsThe framework that we propose to incorporate sta-tistical constraints into wordalignment models isgeneric. It can be applied to complicated modelssuch IBM Model- 4 ... sophis-ticated Model- 4 when proper constraints are activein guiding wordalignmentmodel training. We alsotry to put constraints in Model- 4. As the Equation 1 implies, when a word- to -word generative ... in guiding word alignment training, we compare statistics of different word alignment models. We find that our baseline HMM6 0 0.2 0.4 0.6 0.8 1 0 0.2 0.4 0.6 0.8 1 0 0 .1 0.2 0.3...
... BLEU 1 best 30 bestLang Model (Permutations) 58.8 71. 2Lang Model (TargetProjective) 83.9 95.0Local Tree Order Model 75.8 87.3Local Tree Order Model + Lang Model 92.6 98.0Re-ranking ModelsFeatures ... vocab avg. len vocabMT-train 500K 15 .8 77K 18 .7 79KMT-test 1K 17 .5 – 20.9 –Ref-test 1K 17 .5 – 21. 2 –Table 3: Main data sets used in experiments.target words and/or will not be projective ... first-passmodels in the top part, and the performance of our 15 First-pass models Model BLEU 1 best 30 bestBaseline MT System 33.0 –Lang Model (Permutations) 26.3 28.7Lang Model (TargetCohesive) 31. 7...
... Church 19 91; Brown et al. 19 91; Wu 19 94) used sentence length as the ba-sic feature for alignment. (Kay & Roscheisen 19 93; and Chen 19 93) used lexical information for sentence alignment. Models ... techniques, the DOM tree alignment model, sen-tence alignment model, and candidate web page pair verification model are introduced. 4 DOM Tree AlignmentModel The Document Object Model (DOM) is an ... 4 .1 DOM Tree Alignment Similar to STSG, our DOM tree alignmentmodel supports node deletion, insertion and substitution. Besides, both STSG and our DOM tree align-ment model define the alignment...
... training his stage 1 and stage 2 models. For thestage 2 model, we used a single learning rate of0. 01. For the stage 1 model, we used a sequenceof learning rates: 10 00, 10 0, 10 , and 1. 0. At eachtransition ... words being linked with the estimated condi-tional odds of a cluster of words being linked:LO(w 1 , . . . , wk) =links 1 (w 1 , . . . , wk) + 1 (cooc(w 1 , . . . , wk) − links 1 (w 1 , ... between our stage 1 and stage 2 models is that the stage 1model con-siders each word- to -word link separately, but al-lows multiple links per word, as long as they leadto an alignment consisting...
... of EMNLP, pages 304– 311 .W. A. Gale and K. W. Church. 19 91. Identifying word cor-respondences in parallel texts. In 4th Speech and NaturalLanguage Workshop, pages 15 2 15 7. DARPA.D. Gildea. ... 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. ... modelsin (Brown et al., 19 93), wordalignment has be-come the first step in training moststatistical trans-lation systems, and alignments are useful to a hostof other tasks. The dominant IBM...
... 0.75 31 0.2469 Interpolated 0.7555 0.7084 0.7 312 0.2688 Method 1 0.7986 0. 719 7 0.75 71 0.2429 Method 2 0.8060 0.7388 0.7709 0.22 91 Combination 0. 817 5 0.7858 0.8 013 0 .19 87 Table 2. WordAlignment ... 6. 2 Statistical WordAlignmentModel According to the IBM models (Brown et al., 19 93), the statistical wordalignmentmodel can be generally represented as in equation (1) . ∑=a'e|f,a'e|fa,e|fa,)Pr()Pr()Pr( ... simplified version does not take into account word classes as described in Brown et al. (19 93). ))))(()](([ ))()](([( )|( )|( )Pr(0 ,1 10 ,1 1 11 1 200000∏∏∏∏≠=>≠===−−⋅≠+−⋅=⋅⋅⋅⎟⎟⎠⎞⎜⎜⎝⎛−=majjmajjmjajliiimjjjajjpjdahjcjdahjeftenppmρφφφφφe|fa,(2)ml,...