State of the art
The integration of artificial intelligence and acoustic systems
DOI:
https://doi.org/10.46421/encacelacac.v18i1.7007Keywords:
Artificial Intelligence, Acoustic systemsAbstract
This initial survey investigates the integration of artificial intelligence (AI) and acoustic systems in performance environments, focusing on automation and sound optimization. Using the State-of-the-Art method, studies published between 2018 and 2024 were analyzed, selected based on thematic relevance, technical innovation, and methodological clarity. The sample includes solutions such as intelligent passive systems, adaptive surfaces, and algorithms for real-time reverberation control. Despite technological advances, many studies remain limited to simulations or prototypes, with little validation in real-world contexts. There is also limited participation from architects and sound designers, which restricts more integrated and user-centered approaches. It is concluded that the intersection between AI and acoustics is an emerging field with strong potential to transform the auditory experience in multifunctional spaces.
References
BRANDÃO, E. Acústica de salas: projeto e modelagem. 2.ed. São Paulo: Blucher, 2022.
BUFOOT, M. Intelligent Passive Room Acoustic Technology for Acoustic Comfort in New Zealand Classrooms. 2022. Doctor of Philosophy - School of Future Environments, Auckland University of Technology, Auckland, New Zealand, 2022.
CHU, S. -C.; WU, C. -H.; LIN, E Y. -W. Speech Enhancement Based on Masking Approach Considering Speech Quality and Acoustic Confidence for Noisy Speech Recognition, 2021 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC), Tokio, Japan, p. 536-540, 2021. ISBN: 978-988-14768-9-0. Disponível em: https://ieeexplore.ieee.org/document/9689624. Acesso em: 22 set. 2024.
LONG, M. Architectural Acoustics. 2.ed. United States of America: Elsevier, 2014.
POLETTI, M. A. Active Acoustic Systems for the Control of Room Acoustics, Proceedings of the International Symposium on Room Acoustics, ISRA 2010, Lower Hutt, New Zealand, v. 18, p. 1-10, 2010. Disponível em: https://journals.sagepub.com/doi/10.1260/1351-010X.18.3-4.237. Acesso em: 22 out. 2024.
T’ANNA RAMOS VOSGERAU, D.; PAULIN ROMANOWSKI, J. Review studies: conceptual and methodological implications. Revista Diálogo Educacional, [S. l.], v. 14, n. 41, p. 165–189, 2014. DOI: 10.7213/rde.v14i41.2323. Disponível em: https://periodicos.pucpr.br/dialogoeducacional/article/view/2323. Acesso em: 22 ago. 2024.
SHINDE, P. P; SHAH, S. A Review of Machine Learning and Deep Learning Applications. 2018 Fourth International Conference on Computing Communication Control and Automation (ICCUBEA), Pune, India, p. 1-6, 2018, DOI: 10.1109/ICCUBEA.2018.8697857. Disponível em: https://ieeexplore.ieee.org/abstract/document/8697857. Acesso em: 15 set. 2024. (reviasar e deixar no original)
ZAHEER, R.; AHMAD I.; HABIBI D.; ISLAM, K. Y.; PHUNG Q. V. A Survey on Artificial Intelligence-Based Acoustic Source Identification, ISSN: 2169-3536, em IEEE Access, vol. 11, p. 60078-60108, 2023, DOI: 10.1109/ACCESS.2023.3283982. Disponível em: https://ieeexplore.ieee.org/document/10146285. Acesso em: 15 set. 2024.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2025 ENCONTRO NACIONAL DE CONFORTO NO AMBIENTE CONSTRUÍDO

This work is licensed under a Creative Commons Attribution 4.0 International License.