Using machine learning, engineers “demix” old music, isolating the voices and instruments into separate component tracks—a process very much like unswirling paint. The tracks are then “upmixed,” into something new...and sometimes improved. (From 2021)
, a professional electronics test engineer from Long Island. Kissel didn’t have easy access to a recording studio. But he was a lifelong music fan, and he dreamed of making old tracks sound new.
The first night with his new Mac, Kissel used floppy disks to install an early digital audio workstation called sonicWORX. It was the only software capable of running Pandora Realtime, a plug-in that could selectively boost the volume of vocals on recordings. “It was very advanced for its time,” Kissel says. He wanted to see if the tool could do something more interesting. He loaded up Miss Toni Fisher’s 1959 hit “The Big Hurt” and attempted to pull it apart.
Kissel immersed himself in the developing fields of demixing and upmixing—though the names came later—by moderating forums and maintaining a website chronicling advances in the disciplines. He started playing around with a technique called spectral editing, which allowed people to treat sound as a visual object. Load a song into a spectral editor and you can see all of the recording’s many frequencies, represented as colorful peaks and valleys, laid out on a graph.
Other times, their projects involved focused demixing. When the British online lending company Sunny wanted to use the song “Sunny” by late American R&B singer Bobby Hebb in a commercial, it found that one of the song’s original vocals interrupted the ad’s narration. With Audionamix’s help, the pesky vocals got zapped from existence.
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