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courses:rg:transductive_learning_for_statistical_machine_translation [2010/12/08 22:00] jawaid |
courses:rg:transductive_learning_for_statistical_machine_translation [2010/12/08 22:16] jawaid |
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| * Data filtering is performed on both bilingual and monolingual data to keep only that part of the data which is relevant to the test data. | * Data filtering is performed on both bilingual and monolingual data to keep only that part of the data which is relevant to the test data. | ||
| - | * They used three different evaluation metrics for evaluating translation | + | * They used three different evaluation metrics for evaluating translation |
| + | * Experiments are performed on EuroParl and NIST corpus. On EuroParl corpus the selection and scoring was carried out using importance sampling with normalized score. Three different experiments are performed on the Europarl corpus which didn't produce significant improvement in the accuracy on output translation. Experiments on NIST data are performed using three different test sets where the output translation of each test set yield the best score when threshold-based selection method was combined with confidence estimation as scoring method. | ||
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| ===== What do we dislike about the paper ===== | ===== What do we dislike about the paper ===== | ||
| - | * The technique defined | + | * The semi supervised learning scheme presented |