  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.
