Arbitrary sample rate conversion (ASRC) enables changes of the sampling frequency by flexible, time-varying ratios. It can be utilized advantageously in many applications of audio signal processing. Consequently, numerous algorithms for ASRC have been proposed. However, it is often difficult to choose a minimal-cost algorithm that meets the requirements of a specific application. In this paper, several approaches to ASRC are reviewed. Special emphasis is placed on algorithms that enable optimal designs, which minimize the resampling error with respect to a selectable norm. Evaluations are performed to assess the computational efficiency of different algorithms as a function of the achievable quality. These analyses demonstrate that structures based on oversampling and resampling filters specifically adapted to this structure yield significant performance improvements over established algorithms.
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