Zobrazeno 1 - 10
of 370
pro vyhledávání: '"Simonetta, Federico"'
Speech emotion recognition (SER) is constantly gaining attention in recent years due to its potential applications in diverse fields and thanks to the possibility offered by deep learning technologies. However, recent studies have shown that deep lea
Externí odkaz:
http://arxiv.org/abs/2404.18514
Autor:
Simonetta, Federico, Llorens, Ana, Serrano, Martín, García-Portugués, Eduardo, Torrente, Álvaro
This paper presents a comprehensive investigation of existing feature extraction tools for symbolic music and contrasts their performance to determine the set of features that best characterizes the musical style of a given music score. In this regar
Externí odkaz:
http://arxiv.org/abs/2307.05107
In this work, we introduce musif, a Python package that facilitates the automatic extraction of features from symbolic music scores. The package includes the implementation of a large number of features, which have been developed by a team of experts
Externí odkaz:
http://arxiv.org/abs/2307.01120
This paper proposes a weakly-supervised machine learning-based approach aiming at a tool to alert patients about possible respiratory diseases. Various types of pathologies may affect the respiratory system, potentially leading to severe diseases and
Externí odkaz:
http://arxiv.org/abs/2208.03326
The purpose of this paper is to compare different learnable frontends in medical acoustics tasks. A framework has been implemented to classify human respiratory sounds and heartbeats in two categories, i.e. healthy or affected by pathologies. After o
Externí odkaz:
http://arxiv.org/abs/2208.03084
Autor:
Simonetta, Federico
This Thesis discusses the development of technologies for the automatic resynthesis of music recordings using digital synthesizers. First, the main issue is identified in the understanding of how Music Information Processing (MIP) methods can take in
Externí odkaz:
http://arxiv.org/abs/2205.00941
Motivated by the state-of-art psychological research, we note that a piano performance transcribed with existing Automatic Music Transcription (AMT) methods cannot be successfully resynthesized without affecting the artistic content of the performanc
Externí odkaz:
http://arxiv.org/abs/2203.16294
This study focuses on the perception of music performances when contextual factors, such as room acoustics and instrument, change. We propose to distinguish the concept of "performance" from the one of "interpretation", which expresses the "artistic
Externí odkaz:
http://arxiv.org/abs/2202.12257
Autor:
Pagliuca, Simona *, Schmid, Christoph *, Santoro, Nicole, Simonetta, Federico, Battipaglia, Giorgia, Guillaume, Thierry, Greco, Raffaella, Onida, Francesco, Sánchez-Ortega, Isabel, Yakoub-Agha, Ibrahim, Kuball, Jurgen †, Hazenberg, Mette D †, Ruggeri, Annalisa †, *
Publikováno v:
In The Lancet Haematology June 2024 11(6):e448-e458
Autor:
Wang, Chen, Zeng, Qun, Gül, Zeynep Melis, Wang, Sisi, Pick, Robert, Cheng, Phil, Bill, Ruben, Wu, Yan, Naulaerts, Stefan, Barnoud, Coline, Hsueh, Pei-Chun, Moller, Sofie Hedlund, Cenerenti, Mara, Sun, Mengzhu, Su, Ziyang, Jemelin, Stéphane, Petrenko, Volodymyr, Dibner, Charna, Hugues, Stéphanie, Jandus, Camilla, Li, Zhongwu, Michielin, Olivier, Ho, Ping-Chih, Garg, Abhishek D., Simonetta, Federico, Pittet, Mikaël J., Scheiermann, Christoph
Publikováno v:
In Cell 23 May 2024 187(11):2690-2702