@inproceedings{db09819bd7e647538be148faef9d6f0a,
title = "Evaluation of confidence measures for on-line handwriting recognition",
abstract = "In this paper a writer-independent on-line handwriting recognition system is described comparing the effectiveness of several confidence measures. Our recognition system for single German words is based on Hidden Markov Models (HMMs) using a dictionary. We compare the ratio of rejected words to misrecognized words using four different confidence measures: One depends on the frame-normalized likelihood, the second on a garbage model, the third on a two-best list and the fourth on an unconstrained character recognition. The rating of recognition results is necessary for an unsupervised retraining or adaptation of recognition systems as well as for a user friendly human-computer interaction avoiding excessive call backs.",
author = "Anja Brakensiek and Andreas Kosmala and Gerhard Rigoll",
year = "2002",
doi = "10.1007/3-540-45783-6_61",
language = "English",
isbn = "354044209X",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "507--514",
editor = "{Van Gool}, Luc and {Van Gool}, Luc and {Van Gool}, Luc",
booktitle = "Pattern Recognition - 24th DAGM Symposium, Proceedings",
note = "24th Symposium of the German Pattern Recognition Association, DAGM 2002 ; Conference date: 16-09-2002 Through 18-09-2002",
}