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A Discriminative Training Procedure for Continuous Translation Models
... 3 Discriminative Training of CTMs In SMT, the primary role of CTMs is to help the system in ranking a set of hypotheses so that the top scoring hypotheses correspond to the best translations, where quality ... See full document
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Improved Minimum Phone Error based Discriminative Training of Acoustic Models for Mandarin Large Vocabulary Continuous Speech Recognition
... acoustic models, each of which is normally represented by a continuous density hidden Markov model (HMM), and the corresponding model parameters can be estimated from a corpus of orthographically ... See full document
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Decoder based Discriminative Training of Phrase Segmentation for Statistical Machine Translation
... good translation quality can be trained by using the base SMT ...iterative training algorithm could gradually improve the translation quality of the phrase-based SMT, although the efficiency of the ... See full document
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Target Side Context for Discriminative Models in Statistical Machine Translation
... Discriminative translation models utiliz- ing source context have been shown to help statistical machine translation perfor- ...large training data sizes and results in con- sistent ... See full document
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Discriminative Language Models as a Tool for Machine Translation Error Analysis
... We show translation accuracies of each system before and after training in Table 4. From this table, we can see that the LM increases the accuracy of all dev data, but it does not necessarily have a large ... See full document
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Discriminative Training of 150 Million Translation Parameters and Its Application to Pruning
... using discriminative training with some trans- lation ...trained models performs better than the un- pruned baseline ...inative training makes it possible to achieve smaller models that ... See full document
7
Loss Sensitive Discriminative Training of Machine Transliteration Models
... Perceptron training in three ways: (1) It allows us to consider k-best translitera- tions instead of the best ...machine translation model with more complex ... See full document
5
Minimum Imputed Risk: Unsupervised Discriminative Training for Machine Translation
... The translation models are built using the cor- pus for the IWSLT 2005 Chinese to English trans- lation task (Eck and Hori, 2005), which comprises 40,000 pairs of transcribed utterances in the travel ... See full document
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Extending Statistical Machine Translation with Discriminative and Trigger Based Lexicon Models
... a training cor- pus using the Expectation-Maximization (EM) al- ...both models al- low for a representation of topic-related sentence- level information which puts them close to word sense disambiguation ... See full document
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Unsupervised Discriminative Language Model Training for Machine Translation using Simulated Confusion Sets
... novel procedure to discrimina- tively train a globally normalized log-linear lan- guage model for MT, in an efficient and unsu- pervised ...captures translation alterna- tives that an MT system may face ... See full document
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Continuous Space Translation Models with Neural Networks
... 2.1. Training this model requires to reorder source sentences so as to match the target word or- ...con models; six lexicalized reordering models (Till- mann, 2004; Crego et ... See full document
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Continuous Space Translation Models for Phrase Based Statistical Machine Translation
... the translation model. Both were developed for tuple-based translation systems, ...the training of the model or direct integration into the ...The continuous space translation model ... See full document
10
Joint Feature Selection in Distributed Stochastic Learning for Large Scale Discriminative Training in SMT
... trained translation models and language models by explicitly down-weighting translations that exhibit certain undesired ...for discriminative models have been presented (see Section 2), ... See full document
11
Continuous Space Language Models for Statistical Machine Translation
... In this work, a slightly different procedure was used that operates directly on the translation lat- tices. We believe that this is more efficient than reranking n-best lists since it guarantees that al- ... See full document
8
Large Scale Discriminative Training for Statistical Machine Translation Using Held Out Line Search
... of training data is necessary to reliably estimate their ...language models built from other portions of the training data than are being used for discriminative training), and second, ... See full document
11
Selection of Discriminative Features for Translation Texts
... of training accuracy (i.e. a classifier that accurately predicts training data whose class labels are indeed ...this procedure is known as ...the training set into v subsets of equal ...whole ... See full document
16
Discriminative Training and Maximum Entropy Models for Statistical Machine Translation
... recognition, training the parameters of the acoustic model by optimizing the (average) mu- tual information and conditional entropy as they are defined in information theory is a standard approach (Bahl et ... See full document
8
Hope and Fear for Discriminative Training of Statistical Translation Models
... Because inference is so slow for the translation task, and especially for the CKY-based decoder we are using, parallelization is critical. Batch learning algorithms like MERT are embarrassingly parallel, but ... See full document
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Language Modeling for Code Switching: Evaluation, Integration of Monolingual Data, and Discriminative Training
... LM models based on the final WER of an ASR system side-steps these two issues: it eval- uates the LM on incorrect sentences, and seam- lessly compares LMs with different ...evaluation procedure highly ... See full document
11
The Amirkabir Machine Transliteration System for NEWS 2011: Farsi to English Task
... statistical translation model, Moses is trained with an unconstrained phrase length. Having no limit for the maximum phrase length is feasible in the transliteration case since the number of phrase pairs are much ... See full document
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