arXiv Machine Learning
Jun 2

Quality Audio Prototyping: a prototype system for unified sound retrieval and procedural generation

arXiv:2606. 00629v1 Announce Type: cross Abstract: Sound design workflows frequently oscillate between time-consuming library searches and the complexity of procedural synthesis, with practitioners typically relying on disconnected tools to address each challenge separately.

By Nelly Garcia, Aditya Bhattacharjee, Gabryel Mason-Williams, Israel Mason-Williams, Emmanouil Benetos, Joshua Reiss
arXiv AI
Aug 17

Musical Agent Systems: MACAT and MACataRT

arXiv:2502. 00023v2 Announce Type: replace-cross Abstract: Our research explores the development and application of musical agents, human-in-the-loop generative AI systems designed to support music performance and improvisation within co-creative spaces.

By Keon Ju M. Lee, Philippe Pasquier
arXiv AI
Sep 24

SsgCaps: A controlled dataset for the evaluation of sound scene generation algorithms

SsgCaps is a publicly available dataset of human-engineered sound scenes, each paired with a precisely structured prompt that guides the sampling process. The prompts are drawn from a predefined action-based typology, enabling extensive yet plausible sampling. A comparative quantitative analysis shows only small differences between the open and private versions, supporting the recommendation of the open version for benchmarking sound scene generation algorithms.

By Modan Tailleur (LS2N), Junwon Lee (LS2N), Laurie M Heller (LS2N), Mathieu Lagrange (LS2N), Keunwoo Choi, Brian McFee, Keisuke Imoto, Yuki Okamoto