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Content-based classification, search, and retrieval of audio

    https://ieeexplore.ieee.org/document/556537
    Content-based classification, search, and retrieval of audio. Abstract: Many audio and multimedia applications would benefit from the ability to classify and search for audio based on its characteristics. The audio analysis, search, and classification engine described here reduces sounds to perceptual and acoustical features. This lets users search or retrieve sounds by any …

Content-Based Classification, Search, and Retrieval of Audio

    https://dl.acm.org/doi/10.1109/93.556537
    This article describes an audio analysis, search, and classification engine that reduces sounds to perceptual and acoustical features. Sounds can then be searched or retrieved by any one or a combination of the features, by specifying previously learned classes based on these features, or by selecting or entering reference sounds and asking the engine to retrieve sounds that are …

Content-Based Classification, Search, and Retrieval of Audio

    https://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.352.4198
    The audio analysis, search, and classification engine described here reduces sounds to perceptual and acoustical features. This lets users search or retrieve sounds by any one feature or a combination of them, by specifying previously learned classes based on these features, or by selecting or entering reference sounds and asking the engine to retrieve similar or dissimilar …

Content-Based Classification, Search, and Retrieval of Audio

    https://dl.acm.org/doi/abs/10.1109/93.556537
    Many audio and multimedia applications would benefit from the ability to classify and search for audio based on characteristics of the audio rather than …

Content-based Classification and Retrieval of Audio …

    https://www.microsoft.com/en-us/research/publication/content-based-classification-and-retrieval-of-audio-using-the-nearest-feature-line-method/
    A method is presented for content-based audio classification and retrieval. It is based on a new pattern classification method called the nearest Feature Line (NFL). In the NFL, information provided by multiple prototypes per class is explored. This contrasts to the nearest neighbor (NN) classification in which the query is compared to each prototype individually.

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