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Informes (Departament de Tecnologies de la Informació i les Comunicacions)

Informes (Departament de Tecnologies de la Informació i les Comunicacions)

 

Documents de recerca, en accés obert, com ara working papers, informes de recerca, memòries tècniques, etc., del Departament de Tecnologies de la Informació i les Comunicacions de la UPF.

Recent Submissions

  • Alonso Jiménez, Pablo; Pepino, Leonardo; Batlle-Roca, Roser; Zinemanas, Pablo; Serra, Xavier; Rocamora, Martín (Institute of Electrical and Electronics Engineers (IEEE), 2024)
    We present PECMAE an interpretable model for music audio classification based on prototype learning. Our model is based on a previous method, APNet, which jointly learns an autoencoder and a prototypical network. Instead, ...
  • Hernández Leo, Davinia (2024-01-09)
  • Haki, Behzad; Pelinski, Teresa; Nieto, Marina; Jordà Puig, Sergi (2023-11-20)
    Sampled drums can be used as an affordable way of creating human-like drum tracks, or perhaps more interestingly, can be used as a mean of experimentation with rhythm and groove. Similarly, AI-based drum generation tools ...
  • Plaja-Roglans, Genís; Miron, Marius; Shankar, Adithi; Serra, Xavier (2023-10-30)
    Supervised music source separation systems using deep learning are trained by minimizing a loss function between pairs of predicted separations and ground-truth isolated sources. However, open datasets comprising ...
  • Penarrubia, Carlos; Garrido-Muñoz, Carlos; Valero-Mas, Jose J.; Calvo Zaragoza, Jorge (2023-10-30)
    Optical Music Recognition (OMR) is the field of research that studies how to computationally read music notation from written documents. Thanks to recent advances in computer vision and deep learning, there are successful ...
  • Hernández Leo, Davinia; Ferrer, Josep; Vujovic, Milica; Tabuenca, Bernardo; Ortiz-Beltran, Ariel; Greller, Wolfgang; Carrió, Mar; Moyano Claramunt, Elisabet (2023-10-25)
    Education plays a transversal key role in the UN's Sustainable Development Goals agenda. Educating young people on natural health and the interpretation of scientific evidence can contribute to increased levels of informed ...
  • Haki, Behzad; Kotowski, Błażej; Lee, Cheuk Lun Isaac; Jordà Puig, Sergi (2023-10-24)
    Drummers spend extensive time practicing rudiments to develop technique, speed, coordination, and phrasing. These rudiments are often practiced on "silent" practice pads using only the hands. Additionally, many percussive ...
  • Ramoneda, Pedro; Valero-Mas, Jose J.; Jeong, Dasaem; Serra, Xavier (2023-10-24)
    Estimating the performance difficulty of a musical score is crucial in music education for adequately designing the learning curriculum of the students. Although the Music Information Retrieval community has recently ...
  • Tamer, Nazif Can; Özer, Yigitcan; Müller, Meinard; Serra, Xavier (2023-10-24)
    A descriptive transcription of a violin performance requires detecting not only the notes but also the fine-grained pitch variations, such as vibrato. Most existing deep learning methods for music transcription do not ...
  • Perez, Miguel; Kirchhoff, Holger; Serra, Xavier (2023-10-20)
    Thanks to advancements in deep learning (DL), automatic music transcription (AMT) systems recently outperformed previous ones fully based on manual feature design. Many of these highly capable DL models, however, are ...
  • Morsi, Alia; Tatsumi, Kana; Maezawa, Akira; Fujishima, Takuya; Serra, Xavier (2023-10-20)
    In piano performance, some mistakes stand out to listeners, whereas others may go unnoticed. Former research concluded that the salience of mistakes depended on factors including their contextual appropriateness and a ...
  • Alonso Jiménez, Pablo; Serra, Xavier; Bogdanov, Dmitry (2023-10-03)
    In this work, we address music representation learning using convolution-free transformers. We build on top of existing spectrogram-based audio transformers such as AST and train our models on a supervised task using ...
  • Kim, Hyon; Serra, Xavier (2023-08-31)
    In any piano performance, expressiveness is paramount for effectively conveying the intent of the performer, and one of the most significant aspects of expressiveness is the loudness at the individual key or note level. ...
  • Hernández Leo, Davinia (2023-07-17)
    Quin impacte té la Intel·ligència Artificial (IA) en l’avaluació. Com hem d’adaptar els mètodes d’avaluació per tal que segueixin essent efectius i, a més, posin a prova les competències relacionades amb l’ús de la IA
  • Kim, Hyon; Miron, Marius; Serra, Xavier (2023-05-12)
    Piano is one of the most popular instruments among people that learn to play music. When playing the piano, the level of loudness is crucial for expressing emotions as well as manipulating tempo. These elements convey ...
  • Tamer, Nazif C; Özer, Yigitcan; Müller, Meinard; Serra, Xavier (2023-04-25)
    Pitch estimation of a target musical source within a multi-source polyphonic signal is of great interest for music performance analysis. One possible approach for extracting the pitch of a target source is to first perform ...
  • 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 ...
  • Kim, Hyon; Miron, Marius; Serra, Xavier (2023-01-16)
    Piano is one of the most popular music instruments. During the piano performance, loudness is an important factor for expressiveness, alongside tempo, changes in dynamics play with expectation, convey various emotions, ...
  • Correya, Albin Andrew; Bogdanov, Dmitry; Alonso Jiménez, Pablo; Serra, Xavier (2023-01-10)
    We present Essentia API, a web API to access a collection of state-of-the-art music audio analysis and description algorithms based on Essentia, an open-source library and machine learning (ML) models for audio and music ...
  • 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 ...

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