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Creators/Authors contains: "Bello, J P"

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  1. ; ; ; ; ; (, Proceedings of the 8th Detection and Classification of Acoustic Scenes and Events 2023 Workshop (DCASE2023))
    Accepted Manuscript Full Text Available
  2. ; ; ; ; ; ; ; ; (, Detection and Classification of Acoustic Scenes and Events 2019)
    SONYC Urban Sound Tagging (SONYC-UST) is a dataset for the development and evaluation of machine listening systems for realworld urban noise monitoring. It consists of 3068 audio recordings from the “Sounds of New York City” (SONYC) acoustic sensor network. Via the Zooniverse citizen science platform, volunteers tagged the presence of 23 fine-grained classes that were chosen in consultation with the New York City Department of Environmental Protection. These 23 fine-grained classes can be grouped into eight coarse-grained classes. In this work, we describe the collection of this dataset, metrics used to evaluate tagging systems, and the results of a simple baseline model. 
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    Accepted Manuscript Full Text Available