[PDF] Top 20 Improving IBM Word Alignment Model 1
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Improving IBM Word Alignment Model 1
... the word translation probabilities of Model 1 are a case where there is no clearly better alternative to a uni- form distribution as the smoothing ... See full document
8
Research on Deep Learning HMM Word Alignment
... the model, and used as the character of reference system for the part of Our bilingual parallel corpus contains all bilingual corpus in NIST08 machine translation evaluation and bilingual data mining from the ... See full document
5
Improving Word Alignment Quality using Morpho syntactic Information
... J 1 representing a mapping from the source word f j into the target word e a j ...single-word alignment models as described in (Brown et ...Markov alignment model (Vogel ... See full document
5
Improving Word Alignment Using Linguistic Code Switching Data
... improve word alignment models by incorporating manually-labeled word alignments in addition to sentence ...log-linear model with features from IBM ...increasing word- ... See full document
9
Recurrent Neural Networks for Word Alignment Model
... a word alignment model based on a recurrent neural net- work (RNN), in which an unlimited alignment history is represented by re- currently connected hidden ...Our alignment ... See full document
11
Hidden Markov Tree Model for Word Alignment
... unsupervised word alignment model based on the Hidden Markov Tree (HMT) ...Our model assumes that the alignment variables have a tree structure which is isomorphic to the target ... See full document
9
Active Semi Supervised Learning for Improving Word Alignment
... an alignment link is not present in the gold stan- dard data for the source word, we introduce a NULL alignment constraint, else we select all the links as given in the gold ...mative ... See full document
8
Word Level Confidence Estimation for Machine Translation
... the IBM-1–based and the direct phrase-based confidence measures perform very ...direct model is higher for a lower correct acceptance ratio, whereas the system-based measure performs better for a ... See full document
32
A Probability Model to Improve Word Alignment
... Our algorithm achieved over 44% relative error reduction when compared with IBM-4 used in ei- ther direction and a 25% relative error rate reduc- tion when compared with IBM-4 Refined. It also achieved a ... See full document
8
Discriminative Word Alignment with a Function Word Reordering Model
... dominance model. Formally, this model is similar to the pairwise domi- nance model, except that we use the sentence bound- aries as the anchors instead of the neighboring phrase ...This model ... See full document
11
Alignment Model Adaptation for Domain Specific Word Alignment
... Using these parameters, we build two adaptation models and a translation dictionary on the training data, which are applied to the testing set. The evaluation results on our testing set are shown in Table 1. From ... See full document
8
Large scale Word Alignment Using Soft Dependency Cohesion Constraints
... the model parameters in addition to the word alignments, while in a collapsed sampler the parameters are integrated out and only alignments are ...for IBM Model ...sampling model ... See full document
10
Multi Word Expression Sensitive Word Alignment
... of IBM Model 4 is used as the base- line for word alignment, which we compare to our modified ...GIZA++. Model 4 is incrementally trained by performing 5 iterations of Model ... See full document
9
Improving Statistical Word Alignment with a Rule Based Machine Translation System
... the word similarity has 66,696 ...English word has about two Chinese translations on average. The rows “IBM E-C” and “IBM C-E” show the re- sults obtained by IBM Model-4 when ... See full document
7
Word to word alignment strategies
... Word alignment is the task of identifying trans- lational relations between words in parallel cor- pora with the aim of re-using them in natu- ral language ...of word alignment techniques are ... See full document
7
Context Dependent Alignment Models for Statistical Machine Translation
... context-dependent Model 1 and HMM alignment models, which use context information in the source language to improve estimates of word- to-word translation ...source word contexts ... See full document
9
Diversify and Combine: Improving Word Alignment for Machine Translation on Low Resource Languages
... Word alignment usually serves as the starting point and foundation for a statistical machine translation (SMT) ...of word alignment ...of word alignments based on complementary ... See full document
5
Improving word alignment for low resource languages using English monolingual SRL
... where α represents the inside probabliity, α ′ is the new estimated inside probability, (s, t) are the output language sentence spans, (i, j) are the English SRL parse spans. To ensure that we are not testing on any ... See full document
10
Unsupervised Bilingual POS Tagging with Markov Random Fields
... Figure 1: Bilingual Directed POS induction model When word alignments are monotonic ...the alignment graph), the model of Snyder et ...crossing alignment links pose a problem: ... See full document
8
Towards a Convex HMM Surrogate for Word Alignment
... GIZA++ IBM Model 3 and HMM, as well as the FastAlign IBM Model 2 implementation of (Dyer et ...non-convex alignment models with simpler non-convex ...with IBM Model 2, ... See full document
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