A computational model of the headturn preference procedure: Design, challenges, and insights

Bergmann, C., Ten Bosch, L., & Boves, L. (2014). A computational model of the headturn preference procedure: Design, challenges, and insights. In J. Mayor, & P. Gomez (Eds.), Computational Models of Cognitive Processes (pp. 125-136). World Scientific. doi:10.1142/9789814458849_0010.
The Headturn Preference Procedure (HPP) is a frequently used method (e.g., Jusczyk & Aslin; and subsequent studies) to investigate linguistic abilities in infants. In this paradigm infants are usually first familiarised with words and then tested for a listening preference for passages containing those words in comparison to unrelated passages. Listening preference is defined as the time an infant spends attending to those passages with his or her head turned towards a flashing light and the speech stimuli. The knowledge and abilities inferred from the results of HPP studies have been used to reason about and formally model early linguistic skills and language acquisition. However, the actual cause of infants' behaviour in HPP experiments has been subject to numerous assumptions as there are no means to directly tap into cognitive processes. To make these assumptions explicit, and more crucially, to understand how infants' behaviour emerges if only general learning mechanisms are assumed, we introduce a computational model of the HPP. Simulations with the computational HPP model show that the difference in infant behaviour between familiarised and unfamiliar words in passages can be explained by a general learning mechanism and that many assumptions underlying the HPP are not necessarily warranted. We discuss the implications for conventional interpretations of the outcomes of HPP experiments.
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