Current knowledge of human speech recognition is based on experiments using carefully recorded speech, a quiet testing environment, and undivided attention. Such optimal conditions are rare in everyday life however. Speech recognition under a cognitive load (CL), eg, dual-tasking, has received little attention. Recent findings show that CL has a substantial effect on listeners' relative weighing of lexical and sublexical information, with increased reliance on lexical knowledge under CL. However, there is so far no explanation for this lexical drift. This project aims to identify the mechanisms underlying the effect of CL on speech recognition. It will address the following questions: Does CL alter the nature and extent of activation/competition inside the lexicon? Can the lexical drift under CL be equated with a reduction in phonetic acuity? This project will refine our understanding of the interaction between language and cognition, and provide valuable input for disciplines concerned with the practical aspects of speech recognition in adverse conditions (eg, aging, machine speech recognition).
