Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  demonstrate that an attention-based encoder-decoder model can be used for sentence-level grammatical error identification for the Automated Evaluation of Scientific Writing (AESW) Shared Task 2016. The attention-based encoder-decoder models can be used for the generation of corrections, in addition to error identification, which is of interest for certain end-user applications.  show that a character-based encoder-decoder model is particularly effective, outperforming other results on the AESW Shared Task on its own, and showing gains over a word-based counterpart. Our final model--a combination of three character-based encoder-decoder models, one word-based encoder-decoder model, and a sentence-level CNN--is the highest performing system on the AESW 2016 binary prediction Shared Task.
['Allen Richard Schmaltz', 'Yoon Kim', 'Alexander M. Rush', 'Stuart M. Shieber']
I am writing a research paper on a idea Sentence-Level Grammatical Error Identification as Sequence-to-Sequence Correction
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