Audio fingerprinting robust against reverberation and noise based on quantification of sinusoidality

The implementation of second-screen service requires a technology for quick, accurate content identification. This enables the service to trace the channel of a broadcast program that a user is watching or listening to. One approach is to record an audio signal from the user´s mobile device, and match it with one in a reference database. However, reverberation and exogenous noise distort a recorded audio signal, making accurate identification more difficult. This paper presents a new fingerprinting method for content identification that is robust against reverberation and noise. It employs pseudo-sinusoidal components, which are components that can be regarded as sinusoidal over a short period of time. The method generates a fingerprint that represents the distribution of pseudosinusoidal components in the time-frequency domain. Experimental results show that the method can match a 5-s-long input signal against 792 hours of reference signals in 1.29 s on a single PC, and can identify the correct program with a recall of over 92% and a precision of 100% in a realistic setting.