Browsing by Author "Ellis, Daniel P. W."

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  • A quantitative comparison of different approaches for melody extraction from polyphonic audio recordings
    Gómez Gutiérrez, Emilia, 1975-; Streich, Sebastian; Ong, Bee Suan; Paiva, Rui Pedro; Tappert, Sven; Batke, Jan-Mark; Poliner, Graham; Ellis, Daniel P. W.; Bello, Juan Pablo (Universitat Pompeu Fabra, 2006)
    This paper provides an overview of current state-of-the-art approaches for melody extraction from polyphonic audio recordings, and it proposes a methodology for the quantitative evaluation of melody extraction algorithms. ...
  • General-purpose tagging of Freesound audio with audioSet labels: task description, dataset, and baseline
    Fonseca, Eduardo; Plakal, Manoj; Font Corbera, Frederic; Ellis, Daniel P. W.; Favory, Xavier; Pons Puig, Jordi; Serra, Xavier (Tampere University of Technology, 2018)
    This paper describes Task 2 of the DCASE 2018 Challenge, titled “General-purpose audio tagging of Freesound content with AudioSet labels”. This task was hosted on the Kaggle platform as “Freesound General-Purpose Audio ...
  • Learning sound event classifiers from web audio with noisy labels
    Fonseca, Eduardo; Plakal, Manoj; Ellis, Daniel P. W.; Font Corbera, Frederic; Favory, Xavier; Serra, Xavier (Institute of Electrical and Electronics Engineers (IEEE), 2018)
    As sound event classification moves towards larger datasets, issues of label noise become inevitable. Web sites can supply large volumes of user-contributed audio and metadata, but inferring labels from this metadata ...
  • Melody extraction from polyphonic music signals: approaches, applications and challenges
    Salamon, Justin; Gómez Gutiérrez, Emilia, 1975-; Ellis, Daniel P. W.; Richard, Gaël (Institute of Electrical and Electronics Engineers (IEEE), 2014)
    Melody extraction algorithms aim to produce a sequence of frequency values corresponding to the pitch of the dominant melody from a musical recording. Over the past decade melody extraction has emerged as an active research ...
  • Self-supervised learning from automatically separated sound scenes
    Fonseca, Eduardo; Jansen, Aren; Ellis, Daniel P. W.; Wisdom, Scott; Tagliasacchi, Marco; Hershey, John R.; Plakal, Manoj; Hershey, Shawn; Moore, R. Channing; Serra, Xavier (Institute of Electrical and Electronics Engineers (IEEE), 2021)
    Real-world sound scenes consist of time-varying collections of sound sources, each generating characteristic sound events that are mixed together in audio recordings. The association of these constituent sound events with ...

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