Browsing by Author "Alonso-Jiménez, Pablo"

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  • Buisson, Morgan; Alonso-Jiménez, Pablo; Bogdanov, Dmitry (Institute of Electrical and Electronics Engineers (IEEE), 2022)
    An important amount of work has been devoted to the task of music classification. Despite promising results achieved by convolutional neural networks, there still exists a gap left to be filled for such models to perform ...
  • Alonso-Jiménez, Pablo; Joglar-Ongay, Luis; Serra, Xavier; Bogdanov, Dmitry (Audio Engineering Society, 2019)
    Providing contents within the industry quality standards is crucial for digital music distribution companies. For this reason an excellent quality control (QC) support is paramount to ensure that the music does not contain ...
  • Alonso-Jiménez, Pablo; Bogdanov, Dmitry; Serra, Xavier (ISMIR, 2020)
    We present the integration of various CNN TensorFlow models developed for different MIR tasks into Essentia. This is a continuation of our previous work [1], extending the list of supported models and adding new algorithms ...
  • Valero-Mas, Jose J.; Gallego, Antonio Javier; Alonso-Jiménez, Pablo; Serra, Xavier (Elsevier, 2023)
    Prototype Generation (PG) methods are typically considered for improving the efficiency of the k-Nearest Neighbour (kNN) classifier when tackling high-size corpora. Such approaches aim at generating a reduced version of ...
  • Bogdanov, Dmitry; Lizarraga Seijas, Xavier; Alonso-Jiménez, Pablo; Serra, Xavier (2022-09-27)
    We present MusAV, a new public benchmark dataset for comparative validation of arousal and valence (AV) regression models for audio-based music emotion recognition. To gather the ground truth, we rely on relative ...
  • Bogdanov, Dmitry; Lizarraga Seijas, Xavier; Alonso-Jiménez, Pablo; Serra, Xavier (International Society for Music Information Retrieval (ISMIR), 2022)
    We present MusAV, a new public benchmark dataset for comparative validation of arousal and valence (AV) regression models for audio-based music emotion recognition. To gather the ground truth, we rely on relative judgments ...
  • Alonso-Jiménez, Pablo; Serra, Xavier; Bogdanov, Dmitry (2022-09-22)
    This paper revisits the idea of music representation learning supervised by editorial metadata, contributing to the state of the art in two ways. First, we exploit the public editorial metadata available on Discogs, an ...
  • Alonso-Jiménez, Pablo; Serra, Xavier; Bogdanov, Dmitry (International Society for Music Information Retrieval (ISMIR), 2022)
    This paper revisits the idea of music representation learning supervised by editorial metadata, contributing to the state of the art in two ways. First, we exploit the public editorial metadata available on Discogs, an ...
  • 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 ...
  • Alonso-Jiménez, Pablo; Bogdanov, Dmitry; Pons Puig, Jordi; Serra, Xavier (Institute of Electrical and Electronics Engineers (IEEE), 2020)
    Essentia is a reference open-source C ++ /Python library for audio and music analysis. In this work, we present a set of algorithms that employ TensorFlow in Essentia, allow predictions with pre-trained deep learning models, ...

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