Abstract: The world is filled with a rich diversity of sounds ranging from mundane beeps and whirs to critical cues such as fire alarms or spoken content. These sounds can be inaccessible not only to people with auditory-related disabilities such as those who are deaf or hard of hearing (DHH) but also to hearing people in many situations. We all may find TV dialogue difficult to hear in noisy bars, doorbells inaudible over a vacuum cleaner running, or may miss a phone ringing on a loud train. Jain's work advances sound accessibility by developing interactive systems that leverage advances in machine learning, signal processing, and wearable technology to sense and provide sound feedback. To design these systems, Jain follows a user-centric research process ranging from formative studies, to design and evaluation of prototypes in controlled environments, to crucially, deployments of full systems in the field. In this talk, Jain will outline his work in three areas of sound accessibility: providing awareness about everyday sounds, supporting speech conversations, and improving accessibility of sounds in emerging technologies. He will then conclude with discussing his future plans.

Bio: Dhruv "DJ" Jain is a final year PhD student in Computer Science and Engineering at the University of Washington. His research lies in Human-Computer Interaction (HCI) and focuses on accessibility. He has published over 20 papers in top HCI and accessible computing venues such as CHI, UIST, and ASSETS; seven have been honored with awards. His work has also been covered by the media including by CNN, New Scientist, and Forbes, has invited attention from industries such as Microsoft, Google, and Apple, is included in teaching curricula, and has been released to the public (e.g., one system has over 75,000 users).