How should a robot speak in warm, cold, loud or bright environments? We propose a demonstration that allows participants to experience how varied background ambient contexts (i.e., lighting, sound, background) can affect the acceptability of robot voice styles, including pitch range, speed, and pauses. We demonstrate the technical result of a 3-step voice design process: (a) Collecting human voice data under the varied ambient conditions, (b) Clustering human vocal utterances to identify primary voice styles, and (c) Modifying a robot voice to the clustered voice styles. The demo will allow participants to experience a food service scenario in 6 different ambient conditions, and feel how changing the robot's voice style can affect both intelligibility and social appropriateness. Ultimately, we hope to highlight the importance in adapting a robot's vocal characteristics to ambient contexts, towards deploying robots in the wild.