Digital audio processing is increasingly dependent on algorithms that learn various features and characteristics of audio signals. Neural networks are often used, and they have to be trained with large bodies of audio material so that they can start to behave in a predictable and useful way. Once trained they can be put to work in roles such as distinguishing between live and studio recordings, searching for specific drum sounds in mixes, creating morphed sounds, or emulating existing analog effects.
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