‘Cocktail Party’ Problem Gets a Round of AI

The classic cocktail party problem — how to filter out specific sounds from a variety of background noises — is getting a shot of AI. Human ears do a great job at deciphering sounds from a din because the brain can focus our attention on what we want to hear. Machine-based “sound source separation,” however, has for years befuddled engineers. MIT researchers are training neural networks using music videos to better pinpoint sound sources. The team’s deep learning system “learns directly from a lot of unlabeled YouTube videos, and it gets to know which objects make what kinds of sounds,” said Hang Zhao, an MIT researcher and former NVIDIA Research intern. It’s work that Zhao describes as groundbreaking, and it has wide-ranging applications in speech, audiology, music and robotics.