Isolated-Word Confusion Metrics and the PGPfone Alphabet

Although the confusion of individual phonemes and features have been studied and analyzed since Miller and Nicely [8], there has been little work done on extending this to a predictive theory of word-level confusions. The PGPfone alphabet is a good touchstone problem for developing such word-level confusion metrics. This paper presents some difficulties incurred, along with their proposed solutions, in the extension of phonetic confusion results to a theoretical whole-word phonetic distance metric. The proposed solutions have been used, in conjunction with a set of selection filters, in a genetic algorithm to automatically generate appropriate word lists for a radio alphabet. This work illustrates some principles and pitfalls that should be addressed in any numeric theory of isolated word perception.