@inproceedings{0a1948b9c08845599c490202355b449f,
title = "Use of lexicon density in evaluating word recognizers",
abstract = "We have developed the notion of lexicon density as the true metric to measure expected recognizer accuracy. This metric has a variety of applications, among them evaluation of recognition results, static or dynamic recognizer selection, or dynamic combination of recognizers. We show that the performance of word recognizers increases as lexicon density decreases and that the relationship between the performance and lexicon density is independent of lexicon size. Our claims are supported by extensive experimental validation data.",
author = "Petr Slav{\'i}k and V. Govindaraju",
year = "2000",
doi = "10.1007/3-540-45014-9\_30",
language = "English",
isbn = "3540677046",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "310--319",
editor = "Josef Kittler and Fabio Roli",
booktitle = "Multiple Classifier Systems - First International Workshop, MCS 2000, Proceedings",
address = "Germany",
note = "1st International Workshop on Multiple Classifier Systems, MCS 2000 ; Conference date: 21-06-2000 Through 23-06-2000",
}