A study employed computational and experimental methods to address a number of issues related to the representation and structural organization of spoken words in the mental lexicon. Using a computerized lexicon consisting of phonetic transcriptions of 20,000 words, "similarity neighborhoods" for each of the transcriptions were computed. Among the variables of interest in the computation of the similarity neighborhoods were: (1) the number of words occurring in a neighborhood; (2) the degree of phonetic similarity among the words; and (3) the frequencies of occurrence of the words in the language. The effects of these variables on auditory word recognition were examined in a series of behavioral experiments employing three experimental paradigms: perceptual identification of words in noise, auditory lexical decision, and auditory word naming (i.e., pronunciation). The results of each of these experiments provided strong support for the hypothesis that words are recognized in the context of similar words in the mental lexicon. In particular, it was demonstrated that the number and nature of words in a similarity neighborhood affect the speed and ease with which words are recognized. A "neighborhood probability rule" was developed that adequately predicted identification performance. This rule, based on Luce's (1959) choice rule, combines stimulus word intelligibility, neighborhood confusability, and frequency into a single expression. Based on this rule, a model of auditory word recognition, the "neighborhood activation model," was proposed. This model describes the effects of similarity neighborhood structure on the process of discriminating among the acoustic-phonetic representations of words in memory. (Author/SR)