Use of Lexicon Density in Evaluating Word Recognizers

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.