The research in this revised proposal builds upon work that was completed under R03 DC 04259 """"""""Phonotactic Information in Speech Production,"""""""" which examined how the frequency of occurrence of phonological segments in a word (i.e., phonotactic probability) influenced the speed and accuracy of producing spoken words. The long-term goals of the current project are to better understand the processes and representations used to produce and recognize spoken words. Current models of speech production and word recognition propose multiple levels of representation, such as semantic, lexical, and sub-lexical representations. The research in the current proposal will examine how the frequency of occurrence of a stimulus, and the number of representations that resemble that stimulus (i.e., neighbors) influence the speed and accuracy of processing at each level of representation. The experiments in this proposal are unique in that they will examine the influence of frequency of occurrence and of neighboring representations at several levels of representation, including the semantic, the lexical, and the sub-lexical levels. Furthermore, the research in this proposal will examine these influences in both parts of the spoken language system (i.e, during the recognition and production of spoken words). The results of the proposed research will provide insight into the processes and representations used during the recognition and production of spoken words. Investigating the influence of frequency of occurrence and number of neighbors at each level of representation in both the recognition and the production of spoken language will lead to a better understanding of how different outcomes (e.g., competition versus facilitation) may arise given the demands of the different processing systems. Finally, this research will enable us to build better models of the two systems, as well as better describe the interface between the two systems. That is, the work in this proposal is a first step in the needed direction of integrating models of sub-lexical, lexical, and semantic processing and of models of recognition and production.
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