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Desynchronization degrades the performance of many signal processing algorithms in Wireless Acoustic Sensor Networks. It is mainly caused by the different distances between the source and each node and by the clock phase offset and frequency skew. Classical solutions use clock synchronization protocols and algorithms in the communication layer, but these alternatives do not tackle the lack of synchronization caused by the distances between sources and nodes. In this paper, we present a novel study of the synchronization problem in acoustic sensor networks from a signal processing point of view. First, we propose a theoretical framework that allows us to study the effects of misalignment over any short-time based algorithm, focusing on the requirements of the effective length of the analysis time frame. From this framework, a theoretical synchronization delay is established aimed at reducing the required length of the time frame. Second, two novel alignment methods are developed and are tuned up to reduce the amount of synchronization information required for transmission. The results obtained demonstrate that our proposed methods represent a good solution in terms of performance over the quality of a standard Blind Source Separation algorithm, allowing us to reduce the transmission bandwidth required for synchronization data. [ABSTRACT FROM AUTHOR]