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courses:rg:transductive_learning_for_statistical_machine_translation [2010/12/08 21:25] jawaid |
courses:rg:transductive_learning_for_statistical_machine_translation [2010/12/08 21:48] jawaid |
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| ===== Comments ===== | ===== Comments ===== | ||
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| * The Paper very well describes the transductive learning algorithm, **Algorithm 1** which is inspired by Yarowsky algorithm [1]. | * The Paper very well describes the transductive learning algorithm, **Algorithm 1** which is inspired by Yarowsky algorithm [1]. | ||
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| * Algorithm 1 is based on **Estimate**, | * Algorithm 1 is based on **Estimate**, | ||
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| + | * Estimate function estimates the model parameters or in other words perform training of the system. The authors used three different model for parameters estimation. **Full Re-training**, | ||
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| + | * Scoring function assign a score to each translation t. The scoring functions used in the paper are: **Length-normalized Score** and **Confidence Estimation**. | ||
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| + | * Selection function is used to create additional training data Ti which is used in next iteration i+1 by **Estimate** to augment the original bilingual data. The selection functions used in this paper are: **Importance Sampling**, **Selection using a Threshold** and **Keep All**. | ||
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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. | ||
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