Abstract
Acoustic energy from many different sources is present in the environment at all times. In order for a listener to recognize and understand the auditory environment, it is necessary to disentangle the acoustic wave form and analyze each separate event. This process is referred to as temporal pattern segmentation, or auditory scene analysis (Bregman, 1990). Its task is to break down an auditory scene, or total acoustic input, into a number of coherent segments, each of which has a high probability of coming from the same source. Temporal pattern segmentation (temporal segmentation for short) is a remarkable achievement of the auditory system, playing a fundamental role in auditory perception. It has much in common with visual segmentation of a scene into different objects. Segmentation can be based on either current input or prior knowledge. Segmentation based on current input relies on the similarities of local qualities within the input pattern itself, such as frequency, timing, or amplitude. On the other hand, segmentation based on prior knowledge relies on patterns stored in memory to segregate the auditory input. These two processes occur simultaneously in auditory scene analysis.
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Wang, D.L. (1995). An Oscillatory Correlation Theory of Temporal Pattern Segmentation. In: Covey, E., Hawkins, H.L., Port, R.F. (eds) Neural Representation of Temporal Patterns. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-1919-5_3
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