Read the Room: Adapting a Robot's Voice to Ambient and Social Contexts

How should a robot speak in a formal, quiet and dark, or a bright, lively and noisy environment? By designing robots to speak in a more social and ambient-appropriate manner we can improve perceived awareness and intelligence for these agents. We describe a process and results toward selecting robot voice styles for perceived social appropriateness and ambiance awareness. Understanding how humans adapt their voices in different acoustic settings can be challenging due to difficulties in voice capture in the wild. Our approach includes 3 steps: (a) Collecting and validating voice data interactions in virtual Zoom ambiances, (b) Exploration and clustering human vocal utterances to identify primary voice styles, and (c) Testing robot voice styles in recreated ambiances using projections, lighting and sound. We focus on food service scenarios as a proof-of-concept setting. We provide results using the Pepper robot's voice with different styles, towards robots that speak in a contextually appropriate and adaptive manner. Our results with N=120 participants provide evidence that the choice of voice style in different ambiances impacted a robot's perceived intelligence in several factors including: social appropriateness, comfort, awareness, human-likeness and competency.

I. Introduction

From the moment we wake up, to the moment we go to sleep, our day contains a variety of social situations in different contexts. For example, our first stop may be to the local bustling cafe, picking up our usual coffee to start the day. The end of the day may involve a date night at a fancy romantic restaurant, or a loud, rhythmic nightclub. In either case, these environments contain different lighting and music to set the mood, and people with whom we, hopefully, have the pleasure of interacting.