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Mapping and Visualization with SuperCollider by Marinos Koutsomichalis

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Machine listening

So far we've examined in detail how we can acquire data from various sources. In a visualization context, however, we may encounter situations wherein we will need to control some elements of an animation with respect to some particular characteristic of a signal, for example, their amplitude or their frequency. Yet, these kinds of information are attributes of the signal, rather than parts of it. In other words, we need something to happen not with respect to some existent data (that is, our signal in this context) but with respect to certain characteristics of a data flow. Consider that an audio signal is completely unaware of how loud it is or of what its frequency is. Remember that audio signals are merely streams of numbers ...

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