Conducting speech perception experiments remotely: Some tools, successes, and challenges

Abstract

The use of remote (i.e., web-based) data collection for psycholinguistics research has proliferated in recent years, reflecting the emergence of new tools for promoting high-quality data collection beyond the traditional laboratory environment. This is particularly true this past year, demonstrating one way that the pandemic has transformed research in the short-term. In the long-term, remote approaches will remain a powerful tool in the domain of psycholinguistics, in part because they help (1) promote diversity among participant samples and (2) increase feasibility of the new best practices for promoting reproducibility of research (e.g., larger sample sizes, in-house replications, assessing generalization to novel stimulus sets). However, embracing remote data collection is not without its challenges, especially for speech perception researchers who require some degree of control over the listening environment and participants’ linguistic background. In this talk, I will describe tools, successes, and challenges related to our experiences in conducting remote speech perception experiments for a variety of phenomena (e.g., categorical perception, perceptual learning, talker adaptation, Ganong effect), tasks (e.g., phonetic identification, lexical decision, talker discrimination, transcription), and dependent measures (e.g., reaction time, accuracy, sensitivity, psychometric response functions).