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How should a robot speak in a formal, quiet and dark, or a bright, lively andnoisy environment? By designing robots to speak in a more social andambient-appropriate manner we can improve perceived awareness and intelligencefor these agents. We describe a process and results toward selecting robotvoice styles for perceived social appropriateness and ambiance awareness.Understanding how humans adapt their voices in different acoustic settings canbe challenging due to difficulties in voice capture in the wild. Our approachincludes 3 steps: (a) Collecting and validating voice data interactions invirtual Zoom ambiances, (b) Exploration and clustering human vocal utterancesto identify primary voice styles, and (c) Testing robot voice styles inrecreated ambiances using projections, lighting and sound. We focus on foodservice scenarios as a proof-of-concept setting. We provide results using thePepper robot's voice with different styles, towards robots that speak in acontextually appropriate and adaptive manner. Our results with N=120participants provide evidence that the choice of voice style in differentambiances impacted a robot's perceived intelligence in several factorsincluding: social appropriateness, comfort, awareness, human-likeness andcompetency.

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