Modeling Two-Channel Speech Processing With the EPIC Cognitive Architecture

摘要

An important application of cognitive architectures is to provide human performance models that capture psychological mechanisms in a form that can be programmed to predict task performance of human-machine system designs. Although many aspects of human performance have been successfully modeled in this approach, accounting for multitalker speech task performance is a novel problem. This article presents a model for performance in a two-talker task that incorporates concepts from psychoacoustics, in particular, masking effects and stream formation.