Seamless Audio Melding: Using Seam Carving with Music Playlists

In both studio and live performances, professional music DJs in an increasing number of popular musical genres mix recordings together into continuous streams that progress seamlessly from one song to the next. When done well, these create an engaging and seamless experience, as if they were part of a single performance. This work introduces a new way to provide that continuity using not only beat matching, but also frequency-dependent cross fades. The basis of our technique is derived from the well developed technique of visual-seam carving, most commonly found in computer vision and graphics systems. We adapt visual seam carving to indicate the times at which to transition specific frequencies from one song to the next. Additionally, we also describe a way to invert the melded spectrogram with minimal computation. The entire system works faster than real-time to provide the ability to use this system in live performances.

• Machine Perception