In a computer-crammed space at Savage Beast Technologies, divergent melodies seep softly from headphones worn by young men and women who listen to music with the intensity of submarine sonar operators.
Their job is to discern and define attributes in tunes by artists as diverse as teen diva Hilary Duff and jazz legend Miles Davis.
The listeners classify hundreds of characteristics about each song, including beat, melody, lyrics, tonal palette and dynamics, then plug the data into a music recommendation engine -- software designed to find songs that share similar traits.
