1994/10/21 by David Elworthy, Elworthy, David
Computer Science · #Computation and Language (cs.CL) #FOS: Computer and information sciences #cmp-lg #cs.CL
paper · pdf · doi:10.48550/arxiv.cmp-lg/9410013
Postscript. Appeared in NeMLaP 1994
arxiv created 1994/10/21 · arxiv updated 2009/11/30
A technique for detecting errors made by Hidden Markov Model taggers is described, based on comparing observable values of the tagging process with a threshold. The resulting approach allows the accuracy of the tagger to be improved by accepting a lower efficiency, defined as the proportion of words which are tagged. Empirical observations are presented which demonstrate the validity of the technique and suggest how to choose an appropriate threshold.