A low-complexity audio fingerprinting technique for embedded applications

This paper proposes a new optimized audio-based fingerprinting technology for embedded applications. The target use case is related to TV content synchronization and its numerous applications for Social TV and second screen applications. The proposed technology can be used for automatically identifying the program being watched by capturing the sound of the TV set. It can also be used to know which program is being watched and to precisely estimate the timestamp of the currently broadcast moment with respect to the beginning of the program. This is very useful for second screen applications where notifications ( e.g. quizzes, additional information, commercials) have to be sent to viewers with a perfect synchronization relatively to the broadcast TV program. The robustness of the proposed technique is first evaluated on a large music database and then by considering a realistic use case where this technology is embedded in a smartphone.