Recent interest in high-resolution digital audio has been accompanied by a trend toward higher sampling rates and expanded bit depths, yet the sound quality improvements show diminishing returns, which can be explained by a failure to reconcile human auditory capability with the information capacity of the audio channel. The authors propose an audio capture, archiving, and distribution framework based on sampling kernels having finite length, unlike the “ideal” sinc kernel that has an infinite duration. With these new kernels, the original transient events need not become significantly extended in time when reproduced. This new approach runs contrary to some conventional audio wisdom, such as the complete elimination of aliasing. This paper reviews advances in neuroscience and recent evidence on the statistics of real signals, from which it can be concluded that the conventional criteria may not be helpful. This proposed approach can result in improved time/frequency balance in a high-performance chain whose errors, from the perspective of the human listener, are equivalent to those introduced when sound travels a short distance through air.
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