Front Row: Automatically Generating Immersive Audio Representations of Tennis Broadcasts for Blind Viewers
Gaurav Jain, Basel Hindi, Connor Courtien, Xin Yi Therese Xu, Conrad Wyrick, Michael C. Malcolm, Brian A. Smith
Abstract
Blind and low-vision (BLV) people face challenges watching sports due to the lack of accessibility of sports broadcasts. Currently, BLV people rely on descriptions from TV commentators, radio announcers, or their friends to understand the game. These descriptions, however, do not allow BLV viewers to visualize the action by themselves. We present Front Row, a system that automatically generates an immersive audio representation of sports broadcasts, specifically tennis, allowing BLV viewers to more directly perceive what is happening in the game. Front Row first recognizes gameplay from the video feed using computer vision, then renders players’ positions and shots via spatialized (3D) audio cues. User evaluations with 12 BLV participants show that Front Row gives BLV viewers a more accurate understanding of the game compared to TV and radio, enabling viewers to form their own opinions on players’ moods and strategies. We discuss future implications of Front Row and illustrate several applications, including a Front Row plug-in for video streaming platforms to enable BLV people to visualize the action in sports videos across the Web.
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