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courses:rg:transductive_learning_for_statistical_machine_translation [2010/12/08 23:01]
jawaid
courses:rg:transductive_learning_for_statistical_machine_translation [2010/12/08 23:35] (current)
jawaid
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 ===== Introduction ===== ===== Introduction =====
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 The paper is about the use of transductive semi-supervised methods for the effective use of monolingual data from the source language in order to improve translation quality. Transductive means that they repeatedly translate sentences from the development set or test set and use generated translation to improve the SMT system. Transductive learning is another mean to adapt the SMT system to a new type of text. The paper is about the use of transductive semi-supervised methods for the effective use of monolingual data from the source language in order to improve translation quality. Transductive means that they repeatedly translate sentences from the development set or test set and use generated translation to improve the SMT system. Transductive learning is another mean to adapt the SMT system to a new type of text.
  
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   * Ambiguous terminology is used for defining the feasibility setting in Table 3. '​**'​ is defined as those experiments that produced minimal improvement over the baseline. But, this doesn'​t mean that experiments marked with '​*'​ achieved significant improvement over baseline.   * Ambiguous terminology is used for defining the feasibility setting in Table 3. '​**'​ is defined as those experiments that produced minimal improvement over the baseline. But, this doesn'​t mean that experiments marked with '​*'​ achieved significant improvement over baseline.
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 ===== What do we like about the paper ===== ===== What do we like about the paper =====
  
 +  * Even if the reader doesn'​t have any background knowledge on what transduction learning is, he/she will clearly get the idea about it after reading this paper, how it works in the domain of SMT and what are the features we need to define for training the system. The paper is infact a well written piece of work.
  
  
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   * The semi supervised learning scheme presented in this paper uses the source side test data during training process which limits the use of this technique in different applications. For instance this learning mechanism can not be applied in online translation systems.   * The semi supervised learning scheme presented in this paper uses the source side test data during training process which limits the use of this technique in different applications. For instance this learning mechanism can not be applied in online translation systems.
  
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- +Comments by Bushra Jawaid
  

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