[PDF] Top 20 Better Word Alignments with Supervised ITG Models
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Better Word Alignments with Supervised ITG Models
... small supervised training ...alignment models. We use posteriors from two jointly estimated HMM models to make pruning decisions during ITG in- ference (Liang et ...HMM models: those ... See full document
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Inducing Word Alignments with Bilexical Synchronous Trees
... five word aligners, including IBM models, ITG, the lexical ITG (LITG) of Zhang and Gildea (2005), and our bilexical ITG (BLITG), on a hand-aligned bilingual ...the models were ... See full document
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Combining Unsupervised and Supervised Alignments for MT: An Empirical Study
... The ITG aligner (Haghighi et ...original ITG to handle blocks of words in addition to single ...for word alignment can be traced as far back as to Vogel et ...of supervised data to tweak some ... See full document
7
Exploiting Sentence Similarities for Better Alignments
... using alignments (for ...IBM models (Brown et ...the alignments are often treated as latent variables during learning, as in this work where we treated alignments in the sen- tence level ... See full document
11
Improved Discriminative ITG Alignment using Hierarchical Phrase Pairs and Semi supervised Training
... optimal word alignments and heuristic for phrase ...possible alignments. Birch et al. (2006) propose a better and more efficient method of constraining the search space which does not ... See full document
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Unsupervised Word Alignment by Agreement Under ITG Constraint
... unsupervised word align- ment method that uses a constraint based on Inversion Transduction Grammar (ITG) parse trees to jointly unify two directional mod- ...locating alignments with long dis- ... See full document
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Improving Phrase Based Translation via Word Alignments from Stochastic Inversion Transduction Grammars
... IBM models are also built to allow for fairly “whimsical” reorderings, which are not modeled very well to begin ...corresponds better to the reorderings between natural ...with ITG as well, one of ... See full document
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Combining fast align with Hierarchical Sub sentential Alignment for Better Word Alignments
... different models into one. One (ITG) models distinct language pair well, while the other one (IBM models) models similar language pair ...importing ITG limitations improves ... See full document
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Co regularizing character based and word based models for semi supervised Chinese word segmentation
... Both Models Character-based and word-based models present different behaviors and each one has its own strengths and ...two models supporting the co-regularization in this study are highlight- ... See full document
6
Enhancing Modern Supervised Word Sense Disambiguation Models by Semantic Lexical Resources
... several supervised and knowledge-based systems) collected in (Raganato et ...to better results than in the original distance- based approach proposed in (Melamud et ...different word classes (ALL ... See full document
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Semi supervised Word Sense Disambiguation with Neural Models
... by averaging context vectors of all training sentences of the same sense. We observed in a few cases that the context vector is far from the held-out word’s embedding, especially when the input sentence is not ... See full document
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A Semi Supervised Word Alignment Algorithm with Partial Manual Alignments
... a word alignment framework that can incorporate partial manual align- ...IBM Models with a constrained EM algorithm. The par- tial manual alignments can be obtained by human labelling or ... See full document
10
Better Alignments = Better Translations?
... performs better than or comparable to both baselines, even though it uses a much more limited model than GIZA’s Model ...our models do not per- form as well as GIZA are the ones with a lot of rare ... See full document
8
An Unsupervised Model for Joint Phrase Alignment and Extraction
... alignment models based on inversion transduction grammars (ITGs) (Cherry and Lin, 2007; Zhang et ...change: ITG symbols and phrase pairs are generated in the opposite ...traditional ITG ... See full document
10
Learning Bilingual Word Representations by Marginalizing Alignments
... The word representations our model learns as part of the alignment process are semantically plausible and ...of word representations across multiple languages, future work will focus on applying this model ... See full document
6
Using Word Vectors to Improve Word Alignments for Low Resource Machine Translation
... foreign word vectors in the method, so that if for- eign monolingual data is small or unreliable, we can fall back to only using English word ...the alignments of a token to the common alignment ... See full document
5
Reordering Model Using Syntactic Information of a Source Tree for Statistical Machine Translation
... new word reordering model using syntactic information of a source tree for phrase-based statistical machine ...target-side word order is obtained by rotating nodes of the source-side tree ...target ... See full document
9
Alignment Based Neural Machine Translation
... neural models are used to hypoth- esize translations, word by word, without relying on a pre-existing ...on word alignment concepts that have been part of building state-of-the-art ... See full document
12
Dealing with Spurious Ambiguity in Learning ITG based Word Alignment
... probabilities (collected from FBIS data), relative distances, matchings of high frequency words, matchings of pos-tags, etc. Online training was performed using the margin infused relaxed algo- rithm (Crammer et al., ... See full document
5
Symmetric Word Alignments for Statistical Machine Translation
... many-to-one alignments in one translation direction ...produce alignments which map several English words to one German word (line 5b of Table ... See full document
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