[PDF] Top 20 Using Senses in HMM Word Alignment
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Using Senses in HMM Word Alignment
... Yee Seng Chan and Hwee Tou Ng. 2007. Word sense disambiguation improves statistical machine transla- tion. In In 45th Annual Meeting of the Association for Computational Linguistics (ACL-07, pages 33–40. Philipp ... See full document
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Extentions to HMM based Statistical Word Alignment Models
... to HMM-based alignment ...improves word alignment ...an HMM-based model and a new generative model for target language words that do not have correspondences in the source ... See full document
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HMM Word and Phrase Alignment for Statistical Machine Translation
... Model-4 using GIZA++, we split the bi- texts into two (A-E) or three (C-E) partitions, and train models for each division separately; we find that memory usage is otherwise too ... See full document
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Hierarchical Phrase Based Translation Grammars Extracted from Alignment Posterior Probabilities
... the HMM word-to-word alignment ...target-to-source alignment models is to build two separate systems and combine their output translation ... See full document
10
One Million Sense Tagged Instances for Word Sense Disambiguation and Induction
... the senses tagged with this procedure, we manually evaluated a sub- set of 1,000 randomly selected sense-tagged in- ...Chinese word associated with multiple senses of a target English ...Chinese ... See full document
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Incremental HMM Alignment for MT System Combination
... Indirect HMM (IHMM) alignment, which is one of the best hypothesis alignment methods for conventional MT system combination, in an incremental ...incremental alignment is to align a hypothesis ... See full document
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Hybrid Neural Network Alignment and Lexicon Model in Direct HMM for Statistical Machine Translation
... on word-aligned ...the word alignment toolkit such as GIZA++ is not ...the word-aligned data generated ...network-based HMM is not constrained by these ...direct HMM takes more ... See full document
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Learning Word Sense Distributions, Detecting Unattested Senses and Identifying Novel Senses Using Topic Models
... occurring word sense in a particular domain or corpus, relative to a predefined sense ...given word, from which we can derive a distribution of topics over usages and a predominant ...sense alignment ... See full document
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Fast Collocation Based Bayesian HMM Word Alignment
... We also analysed the number of alignment links that our systems set. It is noteworthy that the Bayesian HMM with NULL words consistently sets much fewer links than all other systems. Taking BHMM as baseline ... See full document
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Towards a Convex HMM Surrogate for Word Alignment
... and HMM, as well as the FastAlign IBM Model 2 implementation of (Dyer et ...turn using models in the source-target and target-source directions; using the same setup as (Simion et ...non-convex ... See full document
10
HMM Word to Phrase Alignment with Dependency Constraints
... the HMM word- to-phrase alignment model with syntac- tic dependency ...current HMM word-to-phrase alignment models on a Phrase-Based Statistical Machine Translation system when ... See full document
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HMM Based Word Alignment in Statistical Translation
... HMM Based Word Alignment in Statistical Translation H M M B a s e d W o r d A l i g n m e n t in S t a t i s t i c a l T r a n s l a t i o n S t e p h a n V o g e l H e r m a n n N e y C h r i s t o p[.] ... See full document
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Research on Deep Learning HMM Word Alignment
... Abstract. Word alignment is an essential step for machine ...traditional word alignment model and the weakness for the context description, the deep learning hidden HMM word ... See full document
5
Unsupervised Acquisition of Predominant Word Senses
... into word sense disambiguation, particularly since the inception of the Senseval evaluation ...a word often has more than one meaning, resolving word sense ambiguity could benefit applications that ... See full document
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Identifying Temporal Orientation of Word Senses
... of word sense disambigua- tion, the classical Lesk algorithm (Lesk, 1986) was used to choose the right sense for a given word in- stead of the most frequent ... See full document
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Word to word alignment strategies
... inconsistent. Using the giza clues both align- ment results are very close in terms of preci- sion and recall whereas a larger difference can be observed using the other two clue settings when applying ... See full document
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Automatic Identification of Infrequent Word Senses
... There is scope for experimentation with other WordNet similarity scores. From earlier experi- ments we noted that the lesk measure produced quite good results, although it is considerably less efficient than jcn as it ... See full document
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Visualizing word senses in WordNet Atlas
... WordNet Atlas is designed for end users like computer sci- entists that are not familiar with computational linguistics and/or WordNet, or other technicians that may want to ex- ploit WordNet in their projects but first ... See full document
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Online Handwritten Devnagari Word Recognition using HMM based Technique
... languages. HMM is widely used in handwritten recognition. HMM based lexicon technique is use for recognition of handwritten Devnagari and Tamil script ...each word in the lexicon as a sequence of ... See full document
5
Using pseudo senses for improving the extraction of synonyms from word embeddings
... The implementation of this convergence pro- cess relies on the P ARAGRAM algorithm, which takes as inputs word embeddings and a set of bi- nary lexical relations accounting for semantic sim- ilarity. P ARAGRAM ... See full document
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