  Although the confusion of individual phonemes and features have been studied
and analyzed since (Miller and Nicely, 1955), 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.
