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Award ID contains: 1955357

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  1. ; ; ; ; ; ; ; (, Journal of Open Source Software)
    Full Text Available 
  2. ; ; ; ; ; (, IEEE)
    Full Text Available 
  3. ; ; (, IEEE)
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  4. ; ; (, IEEE)
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  5. ; ; ; ; ; ; ; (, Zenodo)
    Description This dataset comprises embeddings and captions utilized as the development dataset for DCASE 2024 Challenge Task 7, focusing on 'Environmental Sound Scene Synthesis.' The embeddings are derived from 60 different 4-second audio files formatted as mono 32-bit 32kHz, and are contained in the 'embeddings.tar.xz' file. Captions corresponding to each audio file can be found in 'caption.csv'. This dataset does not comprise the audio files, only the embeddings. Three different types of embeddings are provided: VGGish (vggish), MS-CLAP (clap-2023), and PANNs CNN14 Wavegram-Logmel (panns-wavegram-logmel). Only PANNs CNN14 Wavegram-Logmel (panns-wavegram-logmel) embeddings are used for evaluation in the challenge. For further details, please refer to the challenge website. Contact Modan Tailleur, modan.tailleur@ls2n.fr Mathieu Lagrange, mathieu.lagrange@ls2n.fr 
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  6. ; ; (, International Society for Music Information Retrieval Conference (ISMIR), 2023)
    Accepted Manuscript Full Text Available
  7. ; ; ; ; (, IEEE)
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  8. ; ; ; (, IEEE)
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  9. ; (, Proceedings of the 8th Detection and Classification of Acoustic Scenes and Events 2023 Workshop)
    Accepted Manuscript Full Text Available
  10. ; ; ; ; ; ; ; (, Proceedings of the 8th Detection and Classification of Acoustic Scenes and Events 2023 Workshop (DCASE2023))
    Accepted Manuscript Full Text Available