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The article profiles MIT researcher Paris Smaragdis and his work on machine listening, including ML-based sound source separation and audio understanding. It is a biographical feature with few technical specifics, so readers should look to his group's publications for evidence of what these systems can actually do. The stated goals, such as detecting faulty industrial drills or locating traffic accidents by sound, are plausible but remain aspirational in this piece.
Making machines that can listen
Professor Paris Smaragdis develops computers with superhuman hearing for applications like speech recognition, music understanding, and environmental monitoring.
The crack of a bat accompanied by a roar from the crowd can capture a baseball fan’s attention, even if they miss seeing the home run. Humans may be visual creatures, but we also perceive the world around us by listening to it. To improve artificial perception, MIT Professor Paris Smaragdis SM ’97, PhD ’01 seeks to make machines that can hear and understand sound even better than humans. A machine with super-human hearing could rapidly pinpoint the location of a traffic accident by listening for squealing tires and crunching metal, or identify when an industrial drill might break while it is boring through dense bedrock to dig a geothermal well. “I like to say that I do the same thing the computer vision folks do, but instead I do it for hearing,” says Smaragdis, a professor in the Music and Theatre Arts program of the School of Humanities, Arts, and Social Sciences holding…
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