I examine how lexical frequency, neighborhood density, and phonotactic probability predict word identification, as well as the ways that they relate to each other and to the segments within a word. In a two-alternative forced choice task for identification of monosyllabic English words in noise, accuracy was higher for words with higher lexical frequency, lower neighborhood density, and higher phonotactic probability. However, all three characteristics also differ based on the segments within a word. Adding vowel as a predictor of accuracy largely eliminated the observed effects of phonotactic probability and neighborhood density. This relationship with vowel quality might suggest two directions of effects that can influence misperception patterns and subsequently sound change: Phoneme frequency causing directional confusions, or directional confusions changing phoneme frequency.

We present data on convergence in the Switchboard corpus, ad-dressing differences across measures and across speakers. Wemeasured convergence in four characteristics, to test consis-tency in related and unrelated measures: F0 median, F0 vari-ance, speech rate, and odds of the fillers uh and um. Conver-gence was significant in all measures and exhibited variationboth between individuals and within individuals. Most notably,convergence in one measure was not predictive of convergencein other measures, except between closely related measures.The results demonstrate some of the limitations of generaliz-ing convergence results from one measure to other measures.