Error detection, error correction and performance evaluation in on-line mathematical expression recognition

Kam-Fai Chan, Dit-Yan Yeung

Abstract: Automatic recognition of on-line mathematical expressions is difficult especially when there exist errors. In this paper, we incorporate an error detection and correction mechanism into a parser developed previously by us based on definite clause grammar (DCG). The resulting system can handle lexical, syntactic and some semantic errors. The recognition speed for 600 commonly seen expressions is quite acceptable, ranging from 0.73 to 6 s per expression on a modest workstation. In addition, we propose a performance evaluation scheme which can be used to demonstrate the effectiveness of both the symbol recognition and structural analysis stages by a single measure.