Polyphonic HMI: Mixing Music and Math

So few songs actually become hits—Las Vegas gives you better odds than the music industry! You might as well just put a million dollars on red and spin the wheel . . .
— Ric Wake, Independent Music Producer

In late 2003, the management team of Barcelona-based Polyphonic HMI was preparing to launch an artificial intelligence tool that they believed had the potential to create tremendous value for the music industry. The technology, referred to as Hit Song Science (HSS), analyzed the mathematical characteristics of music (by isolating aspects such as melody, tempo, pitch, rhythm, and chord progression) and compared them with characteristics of past music hits, making it possible to determine a song’s hit potential. Mike McCready, the CEO of Polyphonic, explained:
The music industry has always used two criteria to determine if a song will be a success.
One is that it sounds like a hit. They have professionals at the music labels who are paid to determine if a song sounds like a hit. And two is that they have an idea how they can bring the artist and the song to the market. The problem is that the industry has about a 10% success rate: only one in 10 songs that get promoted ever charts. We add a third criterion—that it has to have optimal mathematical patterns—and significantly increase success rates.
“This piece of technology is truly special,” he raved. “In one of our early tests, HSS generated unusually high scores for Norah Jones, a jazz singer who most industry insiders expected to have limited commercial impact but whose album later rose to the top of the charts. We also correctly predicted each of the hits of rock band Maroon 5.”
Nevertheless, Polyphonic was having its share of problems. Initial sales pitches had met with resistance. “When we tell music executives about the concept,