Computer Engineering Commons^™

Gesture-Based American Sign Language (Asl) Translation System, Kayleigh Moore, Stefano Pecile, Mahdi Yazdanpour

Posters-at-the-Capitol

According to the World Health Organization (WHO), over 5% of the world's population experiences severe hearing loss. Approximately 9 million people in the U.S. are either functionally deaf or have mild-to-severe hearing loss. In this research, we designed and implemented a translation interface which turns American Sign Language (ASL) gestures captured from a pair of soft robotic gloves into text and speech instantaneously.

We used a combination of flex sensors, tactile sensors, and accelerometers to recognize hand gestures and to record hand and fingers positions, movements, and orientations. The digitized captured gestures were then sent to our proposed translation interface …