Passive Temporal Offset Estimation of Multichannel Recordings of an Ad-Hoc Microphone Array

In recent years ad-hoc microphone arrays have become ubiquitous, and the capture hardware and quality is increasingly more sophisticated. Ad-hoc arrays hold a vast potential for audio applications, but they are inherently asynchronous, i.e., temporal offset exists in each channel, and furthermore the device locations are generally unknown. Therefore, the data is not directly suitable for traditional microphone array applications such as source localization and beamforming. This work presents a least squares method for temporal offset estimation of a static ad-hoc microphone array. The method utilizes the captured audio content without the need to emit calibration signals, provided that during the recording a sufficient amount of sound sources surround the array. The Cramer-Rao lower bound of the estimator is given and the effect of limited number of surrounding sources on the solution accuracy is investigated. A practical implementation is then presented using non-linear filtering with automatic parameter adjustment. Simulations over a range of reverberation and noise levels demonstrate the algorithm's robustness. Using smartphones an average RMS error of 3.5 samples (at 48 kHz) was reached when the algorithm's assumptions were met.