Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  presents a new approach to perform the estimation of the translation model probabilities of a phrase-based statistical machine translation system.  use neural networks to directly learn the translation probability of phrase pairs using continuous representations. The system can be easily trained on the same data used to build standard phrase-based systems.  provide experimental evidence that the approach seems to be able to infer meaningful translation probabilities for phrase pairs not seen in the training data, or even predict a list of the most likely translations given a source phrase. The approach can be used to rescore n-best lists, but  also discuss an integration into the Moses decoder. A preliminary evaluation on the English/French IWSLT task achieved improvements in the BLEU score and a human analysis shod that the new model often chooses semantically better translations. Several extensions of this work are discussed.
['Holger Schwenk']
I am writing a research paper on a idea Continuous Space Translation Models for Phrase-Based Statistical Machine Translation
[{"from": "human", "value": "I am writing a research paper on a idea Continuous Space Translation Models for Phrase-Based Statistical Machine Translation"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  presents a new approach to perform the estimation of the translation model probabilities of a phrase-based statistical machine translation system.  use neural networks to directly learn the translation probability of phrase pairs using continuous representations. The system can be easily trained on the same data used to build standard phrase-based systems.  provide experimental evidence that the approach seems to be able to infer meaningful translation probabilities for phrase pairs not seen in the training data, or even predict a list of the most likely translations given a source phrase. The approach can be used to rescore n-best lists, but  also discuss an integration into the Moses decoder. A preliminary evaluation on the English/French IWSLT task achieved improvements in the BLEU score and a human analysis shod that the new model often chooses semantically better translations. Several extensions of this work are discussed."}]