Zobrazeno 1 - 10
of 23
pro vyhledávání: '"Karystinaios, Emmanouil"'
Graph Neural Networks (GNNs) have recently gained traction in symbolic music tasks, yet a lack of a unified framework impedes progress. Addressing this gap, we present GraphMuse, a graph processing framework and library that facilitates efficient mus
Externí odkaz:
http://arxiv.org/abs/2407.12671
This paper approaches the problem of separating the notes from a quantized symbolic music piece (e.g., a MIDI file) into multiple voices and staves. This is a fundamental part of the larger task of music score engraving (or score typesetting), which
Externí odkaz:
http://arxiv.org/abs/2407.21030
In this work, we present Score MUsic Graph (SMUG)-Explain, a framework for generating and visualizing explanations of graph neural networks applied to arbitrary prediction tasks on musical scores. Our system allows the user to visualize the contribut
Externí odkaz:
http://arxiv.org/abs/2405.09241
We propose a new graph convolutional block, called MusGConv, specifically designed for the efficient processing of musical score data and motivated by general perceptual principles. It focuses on two fundamental dimensions of music, pitch and rhythm,
Externí odkaz:
http://arxiv.org/abs/2405.09224
Autor:
Peter, Silvan David, Cancino-Chacón, Carlos Eduardo, Karystinaios, Emmanouil, Widmer, Gerhard
Publikováno v:
10th International Conference on Digital Libraries for Musicology, November 10, 2023, Milan, Italy
Generative models of expressive piano performance are usually assessed by comparing their predictions to a reference human performance. A generative algorithm is taken to be better than competing ones if it produces performances that are closer to a
Externí odkaz:
http://arxiv.org/abs/2401.00471
Autor:
Karystinaios, Emmanouil, Foscarin, Francesco, Jacquemard, Florent, Sakai, Masahiko, Tojo, Satoshi, Widmer, Gerhard
This paper focuses on the nominal durations of musical events (notes and rests) in a symbolic musical score, and on how to conveniently handle these in computer applications. We propose the usage of a temporal unit that is directly related to the gra
Externí odkaz:
http://arxiv.org/abs/2310.14952
Autor:
Zhang, Huan, Karystinaios, Emmanouil, Dixon, Simon, Widmer, Gerhard, Cancino-Chacón, Carlos Eduardo
Publikováno v:
Proceedings of the 24th International Society for Music Information Retrieval Conference (ISMIR 2023), Milan, Italy
Music Information Retrieval (MIR) has seen a recent surge in deep learning-based approaches, which often involve encoding symbolic music (i.e., music represented in terms of discrete note events) in an image-like or language like fashion. However, sy
Externí odkaz:
http://arxiv.org/abs/2309.02567
Roman Numeral analysis is the important task of identifying chords and their functional context in pieces of tonal music. This paper presents a new approach to automatic Roman Numeral analysis in symbolic music. While existing techniques rely on an i
Externí odkaz:
http://arxiv.org/abs/2307.03544
This paper targets the perceptual task of separating the different interacting voices, i.e., monophonic melodic streams, in a polyphonic musical piece. We target symbolic music, where notes are explicitly encoded, and model this task as a Multi-Traje
Externí odkaz:
http://arxiv.org/abs/2304.14848
Autor:
Cancino-Chacón, Carlos, Peter, Silvan, Hu, Patricia, Karystinaios, Emmanouil, Henkel, Florian, Foscarin, Francesco, Varga, Nimrod, Widmer, Gerhard
This paper introduces the ACCompanion, an expressive accompaniment system. Similarly to a musician who accompanies a soloist playing a given musical piece, our system can produce a human-like rendition of the accompaniment part that follows the soloi
Externí odkaz:
http://arxiv.org/abs/2304.12939