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A wireless acoustic sensor network records audio signals with sampling timeand sampling rate offsets between the audio streams, if the analog-digitalconverters (ADCs) of the network devices are not synchronized. Here, weintroduce a new sampling rate offset model to simulate time-varying samplingfrequencies caused, for example, by temperature changes of ADC crystaloscillators, and propose an estimation algorithm to handle this dynamic aspectin combination with changing acoustic source positions. Furthermore, we showhow deep neural network based estimates of the distances between microphonesand human speakers can be used to determine the sampling time offsets. Thisenables a synchronization of the audio streams to reflect the physical timedifferences of flight.

On Synchronization of Wireless Acoustic Sensor Networks in the Presence of Time-varying Sampling Rate Offsets and Speaker Changes