Estimation of Sampling Frequency Mismatch between Distributed Asynchronous Microphones under Existence of Source Movements with Stationary Time Periods Detection

Abstract

In this paper, we propose a method of estimating the sampling frequency mismatch among asynchronous recording devices, even when the sources sometimes move. For a spatially stationary source, there is a method of estimating the sampling frequency mismatch, which appears in the drift of the time difference among the observed digitized signals. When the source moves, however, the change of its location also affects the drift, and the method fails to estimate the mismatch. In the meantime, looking at the practical recording situations, sources sometimes move but sometimes do not move. That is, there should be a set of time frames in which we can assume the spatial stationarity of sources, and to which we are still able to apply the sampling frequency mismatch estimation method. Based on this idea, our proposed method first detects a set of time frames where we can assume the spatial stationary by clustering the time frames using the covariance matrix of each recording device, and then estimates the mismatch by using the detected stationary time frames. Using real recordings with several IC recorders, we show that the proposed method can estimate the sampling frequency mismatch accurately even when the sources sometimes move.