As meetings shifted online during the COVID-19 lockdown, many people found that chattering roommates, garbage trucks and other loud sounds disrupted important conversations. This experience inspired three University of Washington researchers, who were roommates during the pandemic, to develop better earbuds. To enhance the speaker's voice and reduce background noise, "ClearBuds" use a novel microphone system and one of the first machine-learning systems to operate in real time and run on a smartphone. The researchers presented this project June 30 at the ACM International Conference on Mobile Systems, Applications, and Services. "ClearBuds differentiate themselves from other wireless earbuds in two key ways," said co-lead author Maruchi Kim, a doctoral student in the Paul G. Allen School of Computer Science & Engineering.

Scientists have developed wireless earbuds that use AI for background noise cancellation in real time, an advance that may find a range of applications, including in smart-home speakers and tracking robots. The earbuds, named "ClearBuds", were described in a presentation at the Association for Computing Machinery (ACM) International Conference on Mobile Systems, Applications, and Services last month. Researchers from the University of Washington in the US used a novel microphone system and one of the first AI systems of the kind to operate in real-time and run on a smartphone to enhance the speaker's voice and reduce background noise. "ClearBuds differentiate themselves from other wireless earbuds in two key ways," study co-lead author Maruchi Kim, a doctoral student in the Paul G Allen School of Computer Science & Engineering, said. First, he explained that the novel earbuds use a dual microphone array – one in which each earbud creates two synchronised audio streams that provide information and allow spatial separation of sounds coming from different directions with higher resolution.