Browsing by Author "Favory, Xavier"

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  • Ferraro, Andrés; Favory, Xavier; Drossos, Konstantinos; Kim, Yuntae; Bogdanov, Dmitry (Institute of Electrical and Electronics Engineers (IEEE), 2021)
    Modeling various aspects that make a music piece unique is a challenging task, requiring the combination of multiple sources of information. Deep learning is commonly used to obtain representations using various sources ...
  • Favory, Xavier; Fonseca, Eduardo; Font Corbera, Frederic; Serra, Xavier (FRUCT, 2018)
    Properly annotated multimedia content is crucial for supporting advances in many Information Retrieval applications. It enables, for instance, the development of automatic tools for the annotation of large and diverse ...
  • Fonseca, Eduardo; Pons Puig, Jordi; Favory, Xavier; Font Corbera, Frederic; Bogdanov, Dmitry; Ferraro, Andrés; Oramas, Sergio; Porter, Alastair; Serra, Xavier (International Society for Music Information Retrieval (ISMIR), 2017)
    Openly available datasets are a key factor in the advancement of data-driven research approaches, including many of the ones used in sound and music computing. In the last few years, quite a number of new audio datasets ...
  • Fonseca, Eduardo; Favory, Xavier; Pons, Jordi; Font, Frederic; Serra, Xavier (Institute of Electrical and Electronics Engineers (IEEE), 2022)
    Most existing datasets for sound event recognition (SER) are relatively small and/or domain-specific, with the exception of AudioSet, based on over 2 M tracks from YouTube videos and encompassing over 500 sound classes. ...
  • 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 ...
  • Favory, Xavier (Universitat Pompeu Fabra, 2021-03-24)
    Capturing sounds on a recording medium to enable their preservation and reproduction started to be possible during the industrial revolution of the 19th century, originally achieved through mechanic and acoustic devices, ...
  • Favory, Xavier; Drossos, Konstantinos; Virtanen, Tuomas; Serra, Xavier (Institute of Electrical and Electronics Engineers (IEEE), 2021)
    Self-supervised audio representation learning offers an attractive alternative for obtaining generic audio embeddings, capable to be employed into various downstream tasks. Published approaches that consider both audio and ...
  • 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 ...
  • Favory, Xavier; Serra, Xavier (2018)
    Recent advancements in web-based audio systems have enabled sufficiently accurate timing control and real-time sound processing capabilities. Numerous specialized music tools, as well as digital audio workstations, are ...
  • Ramires, António; Chandna, Pritish; Favory, Xavier; Gómez Gutiérrez, Emilia, 1975-; Serra, Xavier (Institute of Electrical and Electronics Engineers (IEEE), 2020)
    We present a deep neural network-based methodology for synthesising percussive sounds with control over high-level timbral characteristics of the sounds. This approach allows for intuitive control of a synthesizer, enabling ...
  • Alonso-Jiménez, Pablo; Favory, Xavier; Foroughmand, Hadrien; Bourdalas, Grigoris; Serra, Xavier; Lidy, Thomas; Bogdanov, Dmitry (2023-04-25)
    In this work, we investigate an approach that relies on contrastive learning and music metadata as a weak source of supervision to train music representation models. Recent studies show that contrastive learning can be ...

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