Results 1 to 10 of about 390,000 (173)
Music Genre Classification with ResNet and Bi-GRU Using Visual Spectrograms [PDF]
arXiv, 2023 Music recommendation systems have emerged as a vital component to enhance user experience and satisfaction for the music streaming services, which dominates music consumption. The key challenge in improving these recommender systems lies in comprehending the complexity of music data, specifically for the underpinning music genre classification.
arxiv
Dynamic Bayesian Networks for Musical Interaction [PDF]
, 2017 We describe in this chapter a consistent set of temporal models that we have developed over the years for analyzing movement in real-time musical interaction. These models are probabilistic and can be unified and generalized under the formalism of dynamic Bayesian networks (DBNs).
Caramiaux, Baptiste +2 more
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PiRhDy: Learning Pitch-, Rhythm-, and Dynamics-aware Embeddings for Symbolic Music [PDF]
, 2020 Definitive embeddings remain a fundamental challenge of computational musicology for symbolic music in deep learning today. Analogous to natural language, music can be modeled as a sequence of tokens. This motivates the majority of existing solutions to explore the utilization of word embedding models to build music embeddings.
arxiv +1 more source
Dynamic aspects of musical imagery
Annals of the New York Academy of Sciences, 2012 Auditory imagery can represent many aspects of music, such as the starting pitches of a tune or the instrument that typically plays it. In this paper, I concentrate on more dynamic, or time‐sensitive aspects of musical imagery, as demonstrated in two recently published studies.
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Complexity Measures of Music [PDF]
, 2017 We present a technique to search for the presence of crucial events in music, based on the analysis of the music volume. Earlier work on this issue was based on the assumption that crucial events correspond to the change of music notes, with the interesting result that the complexity index of the crucial events is mu ~ 2, which is the same inverse ...
arxiv +1 more source
DeepJ: Style-Specific Music Generation [PDF]
, 2018 Recent advances in deep neural networks have enabled algorithms to compose music that is comparable to music composed by humans. However, few algorithms allow the user to generate music with tunable parameters. The ability to tune properties of generated music will yield more practical benefits for aiding artists, filmmakers, and composers in their ...
arxiv +1 more source
The Dynamics of Musical Success
, 2020 Music has tremendous cultural and commercial significance for people the world over. It is one of the oldest human inventions and is among the most popular consumption activities on the planet. The music industry is also of great economic importance with 19 billion dollars in revenue worldwide in 2019.
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Performing Beethoven’s musical dynamics [PDF]
Music Performance Research, 2020 Twentieth-century musicology frequently invoked the music of Beethoven to validate its work-centred, textualist and structuralist agenda. This article re-orients Beethoven’s music towards the performance studies paradigm, which places the music making body and material contexts of performing at the centre of its disciplinary epistemology, by weaving a ...
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On Tonal Dynamics and Musical Meaning
Signata, 2015 In this paper, I explore the logic of tones, as it is expressed in tonal music, in the sense of music based on scales, chords, and phrases, all consisting of tones, that is, the musical sounds we now write as ‘notes’. In particular, I call attention to the force-dynamic relations that determine sequences of chords: ‘chord changes’.
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Dynamic Functional Connectivity in the Musical Brain [PDF]
, 2019 Musical training causes structural and functional changes in the brain due to its sensory-motor demands. This leads to differences in how musicians perceive and process music as compared to non-musicians, thereby providing insights into brain adaptations and plasticity.
Niranjan, Dipankar +3 more
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