Paper Info
Title
Better evaluation for grammatical error correction
Abstract
We present a novel method for evaluating grammatical error correction. The core of our method, which we call MaxMatch (M2), is an algorithm for efficiently computing the sequence of phrase-level edits between a source sentence and a system hypothesis that achieves the highest overlap with the gold-standard annotation. This optimal edit sequence is subsequently scored using F1 measure. We test our M2 scorer on the Helping Our Own (HOO) shared task data and show that our method results in more accurate evaluation for grammatical error correction.
Year
Venue
Keywords
2012
HLT-NAACL
method result,novel method,shared task data,better evaluation,m2 scorer,gold-standard annotation,f1 measure,phrase-level edit,grammatical error correction,source sentence,accurate evaluation
Field
DocType
Citations 
Annotation,Computer science,Error detection and correction,Speech recognition,Artificial intelligence,Natural language processing,Sentence
Conference
73
PageRank 
References 
Authors
3.91
2
2
Name
Order
Citations
PageRank
Daniel Dahlmeier146029.67
Hwee Tou Ng24092300.40