Right for the Job or Opposites Attract? Exploring Cross-Generational User Experiences with “Younger” and “Older” Voice Assistants
Yuto Sawa, Julia Keckeis, Katie Seaborn · Designing Interactive Systems Conference · 2023
Efforts to diversify the design of virtual assistants (VAs) are inspiring new work on voice as a factor of user experience (UX). One trajectory is voice agedness. The Computers are Social Actors (CASA) paradigm suggests that humanlike computer agents are perceived in line with models of people. Notably, work on ageism and similarity attraction theory would predict that agents with “younger” and “older” voices may be treated differently. As a first effort, we explored the UX of a novel “older adult” text-to-speech (TTS) system. Younger (n=16) and older (n=18) people evaluated a VA that switched voices (“young” and “old”) in a storytelling activity. While most preferred the VA's younger-sounding voices on most measures, all tended to rate the “elder” VA as more appropriate within the storytelling context, challenging expectations based on similarity-attractiveness theory. This work provides initial clues about the relationship between age characteristics and age stereotypes for voice UX.