Zobrazeno 1 - 10
of 176
pro vyhledávání: '"Ntalampiras, Stavros"'
The Ricordi archive, a prestigious collection of significant musical manuscripts from renowned opera composers such as Donizetti, Verdi and Puccini, has been digitized. This process has allowed us to automatically extract samples that represent vario
Externí odkaz:
http://arxiv.org/abs/2408.10260
In this study, we aim to determine if generalized sounds and music can share a common emotional space, improving predictions of emotion in terms of arousal and valence. We propose the use of multiple datasets as a multi-domain learning technique. Our
Externí odkaz:
http://arxiv.org/abs/2408.02009
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
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
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:
Colussi, Marco, Ntalampiras, Stavros
After constructing a deep neural network for urban sound classification, this work focuses on the sensitive application of assisting drivers suffering from hearing loss. As such, clear etiology justifying and interpreting model predictions comprise a
Externí odkaz:
http://arxiv.org/abs/2111.10235
Audio-to-score alignment (A2SA) is a multimodal task consisting in the alignment of audio signals to music scores. Recent literature confirms the benefits of Automatic Music Transcription (AMT) for A2SA at the frame-level. In this work, we aim to ela
Externí odkaz:
http://arxiv.org/abs/2107.12854
This work introduces the one-shot learning paradigm in the computational bioacoustics domain. Even though, most of the related literature assumes availability of data characterizing the entire class dictionary of the problem at hand, that is rarely t
Externí odkaz:
http://arxiv.org/abs/2105.00202