A Hierarchical Approach for Audio Capture, Archive, and Distribution

Recent interest in high-resolution digital audio has been accompanied by a trend to higher and higher sampling rates and bit depths, yet the sound quality improvements show diminishing returns and so fail to reconcile human auditory capability with the information capacity of the channel. We propose an audio capture, archiving, and distribution methodology based on sampling kernels having finite length, unlike the “ideal” sinc kernel that extends indefinitely. We show that with the new kernels, original transient events need not become significantly extended in time when reproduced. This new approach runs contrary to some conventional audio desiderata such as the complete elimination of aliasing. The paper reviews advances in neuroscience and recent evidence on the statistics of real signals, from which we conclude that the conventional criteria may be unhelpful. We show that 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.