The use of robots as educational tools has shown to be an effective means of attracting students to science and technology related academic fields. By developing relatable robotic programs, an increase in interest in the field of technology will occur. For this work, researchers focus on the social interaction capabilities of a humanoid social robot, Pepper. The research leverages the Pepper robot platform using the Softbank NAOqi framework along with Google Cloud Speech platform to further develop speech and gesture patterns that will afford for a culturally rich engagement interactive experience. In this work, we will leverage the Pepper platform using the NAOqi framework to further develop speech and gesture patterns that will afford a culturally rich engagement interactive experience. By training culturally relevant vocabulary and gestures into the system, the robot will be able to identify verbal cues that will afford decisions on which language will best serve a particular engagement activity (ie. Social vs. formal, AAVE vs. Standard English). We will be testing this multi‐modal interaction technique by using the Peppers onboard visual system to immediately collect user experience data in the wild.
