Automated diagnosis of non-native English speaker's natural language

Abstract

Typical grammar checking software use some form of natural language parsing to determine if errors exist in the text. If a sentence is found ungrammatical, the grammar checker usually seeks a single grammatical error as an explanation. For non-native speakers of English, it is possible that a given sentence contain multiple errors and grammar checkers may not adequately explain these mistakes. This paper presents GRADES, a diagnostic program that detects and explains grammatical mistakes made by non-native English speakers. GRADES performs its diagnostic task, not through parsing, but through the application of classification and pattern matching rules. This makes the diagnostic process more efficient than other grammar checkers. GRADES is envisioned as a tool to help non-native English speakers learn to correct their English mistakes, but is also a demonstration that grammar checking need not rely on parsing techniques.