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Audio categorization; Audio indexing; Audio recognition
Audio classification aims at classifying a piece of audio signal into one of the pre-defined semantic classes. It is typically realized as a combination of a learning step to learn a statistical model of each semantic class, and an inference step to estimate which semantic class is closest to the given piece of audio signal.
Audio classification associates semantic labels with audio signals, and can also be referred to as audio indexing, audio categorization or audio recognition. As such, audio classification plays an important role in facilitating search and retrieval in large-scale audio collections (databases). Semantic labels are used to represent semantic classes or semantic concepts, which can be defined at different abstraction and complexity levels. Typical examples of basic semantic audio classes are speech, music, environmental sounds, and silence, which can be detected rather...
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