2018 AttentionbasedEncoderDecoderNet

• (Ahmadi, 2018) ⇒ Sina Ahmadi. (2018). “Attention-based Encoder-Decoder Networks for Spelling and Grammatical Error Correction.” In: arXiv preprint arXiv:1810.00660.

Subject Headings: Attention Mechanism Encoder-Decoder Neural Networks; Spelling Error Correction Task; Grammatical Error Correction Task

Cited By

• http://scholar.google.com/scholar?q=%222018%22+Attention-based+Encoder-Decoder+Networks+for+Spelling+and+Grammatical+Error Correction.

Quotes

Abstract

Automatic spelling and grammatical correction systems are one of the most widely used tools within natural language applications. In this thesis, we assume the task of error correction as a type of monolingual machine translation where the source sentence is potentially erroneous and the target sentence should be the corrected form of the input. Our main focus in this project is building neural network models for the task of error correction. In particular, we investigate sequence-to-sequence and attention-based models which have recently shown a higher performance than the state-of-the-art of many language processing problems. We demonstrate that neural machine translation models can be successfully applied to the task of error correction. While the experiments of this research are performed on an Arabic corpus, our methods in this thesis can be easily applied to any language.

References

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	Author	volume	Date Value	title	type	journal	titleUrl	doi	note	year
2018 AttentionbasedEncoderDecoderNet	Sina Ahmadi			Attention-based Encoder-Decoder Networks for Spelling and Grammatical Error Correction.						2018