Tuesday, March 29, 2022
2:00 - 4:00 PM (PST) on Zoom
Abstract:
Whether intended or not, we quickly and automatically render judgments of the people we encounter. From the sound of a voice alone, we make inferences about the social categories that may be applied to a speaker (e.g. gender, language status, etc.), their current emotional state (e.g. sad, angry), relevant traits they may possess (e.g., friendly, trustworthy, intelligent), and their potential attitude or stance toward a task, toward ourselves or others. As speakers, we also engage in behaviors to manage the impressions we make on others. In fact, there is some consensus over the importance of emphasizing one's likability and competence, particularly during initial encounters (Cuddy, Fiske, Glick, 2008). While some impression management behaviors involve the propositional content of our speech, i.e. what we say, other behaviors involve paralinguistic aspects of speech, i.e. how we say it. But what acoustic features of speech do people change when they want to sound likable and competent? And in what ways do they change them? These questions lie at the heart of active research in fields as diverse as human-computer interaction, education and ethology. Answering them necessarily engages us in a range of measurement and other methodological problems. An overview will be provided of past and current efforts to investigate how speakers vary the acoustic properties of their speech to influence the impressions they make. Emphasis is given to those acoustic properties of speech that support likability and competence impressions as a step toward automating their detection.
About the speaker:
Seth Corrigan's formal training is in measurement science with a focus on designing and developing digital learning applications, measures, psychometric modeling and machine learning. He has experience leading design and development of traditional and automated assessment systems for national markets, and a successful track record of designing and developing measures for complex and challenging constructs; examples include a range of soft skills, complex problem solving, oral communication, collaboration and written argumentation. Over the last decade he has designed and developed several digital games and simulations that utilize machine learning and psychometrics to simultaneously teach and assess, as well as making contributions to an AI driven embodied tutor for mathematics with automated gesture and speech. From 2014-2016 he was a member of the Embodied Design Research Laboratory at the University of California, Berkeley. From 2016-2018 Seth was a visiting scholar at Indiana University's Creativity Lab. He is currently a visiting researcher with New York University's GovLab identifying means to support public participation in design of measures of 21st Century and soft skills. His work has been funded by the Bill and Melinda Gates Foundation, the National Science Foundation (NSF), the Hewlett Foundation, the Google Foundation, the U.S. National Oceanic and Atmospheric Administration (NOAA), as well as the Carnegie Corporation, among others. His most recent publication is a report for USAID on simulation and game-based technologies for supporting and measuring civic engagement in new democracies.