Synchronization of Signals with Sampling Rate Offset and Missing Data Using Dynamic Programming Matching

In this paper, we propose a blind synchronization method for signals with sampling rate offset (SRO) and missing data, which occasionally occurs in distributed recording for acoustic scene classification. In our method, the correspondence between short-time frames is first estimated using cross-correlation and dynamic programming (DP) matching. Then, two methods for producing synchronized signals are compared. The first method is based on the overlap-add along the DP path, while the second method uses the DP path only to identify missing data positions and compensates for the SRO with a linear phase model. The performance of these methods is evaluated through experiments. The results are promising, and further applications to acoustic scene classification are expected.