Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Word alignment methods can gain valuable guidance by ensuring that their alignments maintain cohesion with respect to the phrases specified by a monolingual dependency tree. Hover, this hard constraint can also rule out correct alignments, and its utility decreases as alignment models become more complex.  use a publicly available structured output SVM to create a max-margin syntactic aligner with a soft cohesion constraint. The resulting aligner is the first, to our knowledge, to use a discriminative learning method to train an ITG bitext parser.
['Colin Cherry', 'Dekang Lin']
I am writing a research paper on a idea Soft Syntactic Constraints for Word Alignment through Discriminative Training
[{"from": "human", "value": "I am writing a research paper on a idea Soft Syntactic Constraints for Word Alignment through Discriminative Training"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Word alignment methods can gain valuable guidance by ensuring that their alignments maintain cohesion with respect to the phrases specified by a monolingual dependency tree. Hover, this hard constraint can also rule out correct alignments, and its utility decreases as alignment models become more complex.  use a publicly available structured output SVM to create a max-margin syntactic aligner with a soft cohesion constraint. The resulting aligner is the first, to our knowledge, to use a discriminative learning method to train an ITG bitext parser."}]