Zobrazeno 1 - 10
of 109
pro vyhledávání: '"Shlomo DUBNOV"'
Publikováno v:
Journal of Creative Music Systems, Vol JCMS Special Issue of the first Conference on AI Music Creativity, Iss 1 (2022)
Generative musical models often comprise of multiple levels of structure, presuming that the process of composition moves between background to foreground, or between generating musical surface and some deeper and reduced representation that governs
Externí odkaz:
https://doaj.org/article/a92d8837bd194ac09ad5e845abdc7376
Autor:
Shlomo Dubnov
Publikováno v:
Algorithms, Vol 15, Iss 12, p 484 (2022)
Capturing long-term statistics of signals and time series is important for modeling recurrent phenomena, especially when such recurrences are a-periodic and can be characterized by the approximate repetition of variable length motifs, such as pattern
Externí odkaz:
https://doaj.org/article/89dcb10291b2496b91d3049124e87c20
Publikováno v:
Physical Sciences Forum
Physical Sciences Forum, 2023, 5 (1), pp.49. ⟨10.3390/psf2022005049⟩
Physical Sciences Forum, 2023, 5 (1), pp.49. ⟨10.3390/psf2022005049⟩
International audience; Music improvisation is the ability of musical generative systems to interact with either another music agent or a human improviser. This is a challenging task, as it is not trivial to define a quantitative measure that evaluat
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::002edb8c5c57b4caa9954b07246fca4e
https://hal.science/hal-04010744/document
https://hal.science/hal-04010744/document
Autor:
Ke Chen, Hao-Wen Dong, Yi Luo, Julian Mcauley, Taylor Berg-Kirkpatrick, Miller Puckette, Shlomo Dubnov
Choral music separation refers to the task of extracting tracks of voice parts (e.g., soprano, alto, tenor, and bass) from mixed audio. The lack of datasets has impeded research on this topic as previous work has only been able to train and evaluate
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::62c6cfb95591fa5bdb3518dcd67a41fb
Publikováno v:
2022 IEEE 5th International Conference on Multimedia Information Processing and Retrieval (MIPR)
2022 IEEE 5th International Conference on Multimedia Information Processing and Retrieval (MIPR), IEEE, Aug 2022, CA (virtual), United States. pp.121-126, ⟨10.1109/MIPR54900.2022.00028⟩
2022 IEEE 5th International Conference on Multimedia Information Processing and Retrieval (MIPR), IEEE, Aug 2022, CA (virtual), United States. pp.121-126, ⟨10.1109/MIPR54900.2022.00028⟩
International audience; In this paper we survey the methods for control and cre- ative interaction with pre-trained generative models for au- dio and music. By using reduced (lossy) encoding and sym- bolization steps we are able to examine the level
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b69c3a9de31fe3856272ee5bbe9a5da1
https://hal.science/hal-04010750/file/MIPR_Invited_paper.pdf
https://hal.science/hal-04010750/file/MIPR_Invited_paper.pdf
Autor:
Surges, G., Shlomo DUBNOV
Publikováno v:
Scopus-Elsevier
A system is described which uses the Audio Oracle algorithm for music analysis and machine improvisation. Some improvements on previous Factor Oracle-based systems are presented, including automatic model calibration based on measures from Music Info
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::85b3102fdcbfa5b4e00a13f23913ee7c
https://doi.org/10.1609/aiide.v9i5.12653
https://doi.org/10.1609/aiide.v9i5.12653
Publikováno v:
Scopus-Elsevier
With the advancement in Deep Learning technologies, computers today are able to achieve unimaginable success in several domains involving images and audio. One such area in 3D audio where the applications of deep learning can be promising is in binau
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f2f3abf4711f96352559acd6af268589
Publikováno v:
ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2022, pp. 646-650
ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Audio classification is an important task of mapping audio samples into their corresponding labels. Recently, the transformer model with self-attention mechanisms has been adopted in this field. However, existing audio transformers require large GPU
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::560c72e4c659ddeb4bd0a4ac810f3f31
Autor:
Conan Lu, Shlomo Dubnov
We propose ChordGAN, a generative adversarial network that transfers the style elements of music genres. ChordGAN seeks to learn the rendering of harmonic structures into notes by embedding chroma feature extraction within the training process. In no
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6bd4b494deb16c330916b09fd005b7dd
Autor:
Ross Greer, Shlomo Dubnov
Publikováno v:
Scopus-Elsevier
Shlomo DUBNOV
Shlomo DUBNOV
Nonverbal communication, in particular eye contact, is a critical element of the music classroom, shown to keep students on task, coordinate musical flow, and communicate improvisational ideas. Unfortunately, this nonverbal aspect to performance and
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::26d72ccb2890432015b5a536db046f4f
http://arxiv.org/abs/2105.10047
http://arxiv.org/abs/2105.10047