[PDF] Top 20 Training Data in Statistical Machine Translation - the More, the Better?
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Training Data in Statistical Machine Translation - the More, the Better?
... on training and test data and on all processing ...where translation domain changes dynamically and a large number of language pairs is involved, a framework criteria for the training and test ... See full document
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Better Statistical Machine Translation through Linguistic Treatment of Phrasal Verbs
... This article describes a linguistically in- formed method for integrating phrasal verbs into statistical machine translation (SMT) systems. In a case study involving English to Bulgarian SMT, we show ... See full document
6
Improving Statistical Machine Translation Performance by Training Data Selection and Optimization
... the training data offline to make it match the test data better in domain, topic and style, thus improving the translation ...the training data into several do- mains and ... See full document
8
Better Hypothesis Testing for Statistical Machine Translation: Controlling for Optimizer Instability
... Statistical machine translation systems consist of a model whose parameters are estimated to maximize some objective function on a set of development ...rate training (Och, 2003) and Markov ... See full document
6
Towards Effective Use of Training Data in Statistical Machine Translation
... For Model 1 filtering, we trained IBM Model 1 on Europarl and NewsCommentary concatenated, in both directions, and scored the sentences in the se- lection corpus using the length-normalised sum of the IBM Model scores. ... See full document
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Passive and Pervasive Use of Bilingual Dictionary in Statistical Machine Translation
... in statistical ma- chine translation: (i) the passive approach of appending the parallel training data with a bilingual dictionary and (ii) the per- vasive approach of enforcing ... See full document
5
Minimum Error Rate Training in Statistical Machine Translation
... a better scoring point in the param- eter space by making a one-dimensional line min- imization along the directions given by optimizing one parameter while keeping all other parameters ... See full document
8
Phrase Training Based Adaptation for Statistical Machine Translation
... performs better than the flat model, there- fore, they conclude that retaining the original rela- tive frequency probabilities of the TM is important for good ...phrase training based adaptation and the ... See full document
6
A Systematic Comparison of Training Criteria for Statistical Machine Translation
... The maximum likelihood (MLE) criteria perform somewhat worse under MAP decoding. Interest- ingly, the MBR decoding can compensate this to a large extent: all criteria achieve a Bleu score of about 18.9% on the ... See full document
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Preprocessing on bilingual data for Statistical Machine Translation
... As training data is finite and the number of possible sentences is not, it will always be possible to construct a sentence that has one or more n-grams that do not occur in the training ... See full document
47
Online Large Margin Training for Statistical Machine Translation
... achieve better oracle translations. The training took nearly 1 day using 8 cores of ...The translation quality is eval- uated by case-sensitive NIST (Doddington, 2002) and BLEU (Papineni et ... See full document
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Urdu to English Machine Translation using Bilingual Evaluation Understudy
... is Statistical Machine Translation ...in machine translation between languages with significant word order differences ...Based Machine Translation (EBMT) that translates ... See full document
8
Discriminative Training and Maximum Entropy Models for Statistical Machine Translation
... • BLEU score: This score measures the precision of unigrams, bigrams, trigrams and fourgrams with respect to a whole set of reference trans- lations with a penalty for too short sentences (Papineni et al., 2001). Unlike ... See full document
8
Improvement of the Results of Statistical Machine Translation System using Anusaaraka
... Statistical Machine Translation is the one of the most excelled machine translation approaches based on the concept of statistical models, whose parameter are estimated by ... See full document
7
Parametric Weighting of Parallel Data for Statistical Machine Translation
... the data (55M words, ...the data (24M words, part Recent ...of data that is further away from the time period of the test data (25M words, part Ancient 2), we observe a significant loss in ... See full document
9
Reducing the Impact of Data Sparsity in Statistical Machine Translation
... a better method for sense selection and extending this con- cept for more language ...choosing more appro- priate sense when the translation model is trained on a bigger data ... See full document
6
Linguistically Augmented Bulgarian to English Statistical Machine Translation Model
... Including more factors (especially the in- formation from the dependency parsing) drops the results because of the sparseness effect over the dataset, which is consistent with the automatic evaluation BLEU ... See full document
10
More Linguistic Annotation for Statistical Machine Translation
... The main difference to our baseline system from the submission from last year is the use of ad- ditional training data: larger releases of the News Commentary, Europarl, Czeng, and monolingual news corpora. ... See full document
6
Decoder based Discriminative Training of Phrase Segmentation for Statistical Machine Translation
... reference translation, and then used only the phrase segments in the labeled data when referring the phrase table during the decoding ...the translation system learns the segmentation boundaries ... See full document
10
Locally Training the Log Linear Model for SMT
... In statistical machine translation, minimum error rate training (MERT) is a standard method for tuning a single weight with regard to a given development ...local training method to ... See full document
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