A computational analysis of uniqueness points in auditory word recognition

Abstract

To determine the extent to which words in isolation may be recognized prior to their offsets, uniqueness points or optimal discrimination points were computed for all words in a 20,000-word computerized lexicon with more than two phonemes. The results of this analysis revealed that the frequency-weighted probability of a word's diverging from all other words in the lexicon prior to the last phoneme was only 39. This finding suggests that an optimally efficient strategy of word recognition may be severely limited in scope due to structural properties of the mental lexicon. © 1986 Psychonomic Society, Inc.