Fast audio fingerprint comparison for real-time TV-channel recognition applications

This paper considers IRTR (Improved Real-Time TV-channel Recognition), a new method aimed at recognizing in real-time (live) what people is watching on TV, similarly to the action performed by Audience investigations, but without any TV user active interaction. IRTR uses only the audio signal of the TV program recorded through smartphones and is independent of the specific smartphone technology. It is performed through two main steps: i) fingerprint extraction and ii) TV channel real-time identification. This paper proposes a likelihood estimation-based algorithm aimed at performing the second step. The computational time of the proposed approach has been evaluated through real measures and shows really satisfying results.