Paper: Exploiting Syntactic and Distributional Information for Spelling Correction with Web-Scale N-gram Models

ACL ID D11-1119
Title Exploiting Syntactic and Distributional Information for Spelling Correction with Web-Scale N-gram Models
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2011
Authors

We propose a novel way of incorporating de- pendency parse and word co-occurrence in- formation into a state-of-the-art web-scale n- gram model for spelling correction. The syn- tactic and distributional information provides extraevidenceinadditiontothatprovidedbya web-scale n-gram corpus and especially helps with data sparsity problems. Experimental results show that introducing syntactic fea- tures into n-gram based models significantly reduceserrorsby up to 12.4%over the current state-of-the-art. The word co-occurrence in- formation shows potential but only improves overall accuracy slightly.