Whole-word phonetic distances and the PGPfone alphabet

Abstract

Like many cryptosystems, PGPfone requires a method of reliably exchanging binary data over noisy phone lines. This paper describes a method of encoding binary data into a "radio alphabet" using a feature-based distance metric to measure phonetic confusibility, then using this metric in a genetic algorithm to select appropriate words from a larger list of candidate words. This work indicates several larger issues that should be addressed in any (human) language engineering project.