Preliminary results for an operational definition and methodology for predicting large vocabulary DUR confusability from phonetic transcriptions

The inherent complexity of a vocabulary for discrete-utterance recognition (DUR) is qualitatively easy to surmise when the vocabulary size is small. For large vocabularies a quantifying methodology is needed. We propose an operational definition and methodology for empirically deriving a measure of confusability based only on phonetic transcriptions. There are five components - 1) an appropriate (for DUR) set of alphaphonetics and a transcription data-base and methodology, 2) a phonemic distance metric, 3) a mechanism for aligning transcriptions, 4) an utterance-level, pairwise-confusion metric, and 6) a vocabulary confusion measure. These five facets are briefly described, and preliminary results for the first 700 words of the Brown Corpus are presented.