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The collaboration between artificial intelligence (AI) and acoustics marks a groundbreaking advancement in creating optimal soundscapes across various environments. This article explores the profound impact of AI on reshaping acoustics, transitioning from an art form to a precise science. Through AI-driven techniques, architects and designers can now analyze architectural parameters and materials to achieve ideal sound properties in room acoustics design. Additionally, AI plays a pivotal role in noise reduction and control, mitigating unwanted sounds and enhancing auditory clarity. Its application extends to improving speech intelligibility in noisy environments, particularly in modern workplaces, and facilitating environmental noise monitoring for urban planning and noise pollution mitigation. With numerous case studies highlighting AI’s transformative influence, this article provides valuable insights into future innovations and the potential for AI to revolutionize our sonic surroundings. In essence, AI harnesses computer systems to simulate human intelligence processes, optimizing sound environments and revolutionizing the field of acoustics.
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193--209
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Bibliogr. 32 poz., rys., zdj.
Twórcy
autor
- Katedra Inżynierii Środowiska, Wydział Geoinżynierii, Uniwersytet Warmińsko-Mazurski, ul. Warszawska 117a, 10-720 Olsztyn, adam.starowicz@uwm.edu.pl
autor
- Katedra Inżynierii Środowiska, Wydział Geoinżynierii, Uniwersytet Warmińsko-Mazurski, ul. Warszawska 117a, 10-720 Olsztyn
Bibliografia
- ABDULJABBAR R., DIA H., LIYANAGE S., BAGLOEE S.A. 2019. Applications of artificial intelligence in transport: An overview. Sustainability, 11(1): 189.
- ALDOSERI A., AL-KHALIFA K.N., MAGID HAMOUDA A. 2023. Re-thinking data strategy and integration for artificial intelligence: Concepts, opportunities, and challenges. Applied Sciences, 13(12): 7082.
- ANTOSHCHUK S., KOVALENKO M., SIECK J. 2018. Creating an interactive musical experience for a concert hall. International Journal of Computing, 17(3): 143-152.
- BLAGEC K., DORFFNER G., MORADI M., SAMWALD M. 2020. A critical analysis of metrics used for measuring progress in artificial intelligence. Computer Science. Artificial Intelligence. https://arxiv.org/abs/2008.02577. https://doi.org/10.48550/arXiv.2008.02577
- CIABURRO G., IANNACE G., ALI M., ALABDULKAREM A., NUHAIT A. 2021. An artificial neural network approach to modelling absorbent asphalts acoustic properties. Journal of King Saud University – Engineering Sciences, 33(4): 213-220.
- COKER K., SHI C. 2019. A survey on virtual bass enhancement for active noise cancelling headphones. ICCAIS 2019 – 8th International Conference on Control, Automation and Information Sciences.
- FALCÓN PÉREZ R. 2018. Machine-learning-based estimation of room acoustic parameters. Thesis supervisor: V. Pulkki, thesis advisor L. McCormack. School of Electrical Engineering, Aalto University.
- GLIGOREA I., CIOCA M., OANCEA R., GORSKI A.T., GORSKI H., TUDORACHE P. 2023. Adaptive learning using artificial intelligence in e-learning: A literature review. Education Sciences, 13(12): 1216.
- HARUVI A., KOPITO R., BRANDE-EILAT N., KALEV S., KAY E., FURMAN D. 2021. Modeling the effect of background sounds on human focus using brain decoding technology. bioRxiv. The Preprint Server for Biology. https://doi.org/10.1101/2021.04.02.438269
- High-performance modelling and simulation for Big Data Applications. Selected results of the COST Action IC1406 cHiPSet. 2019. Eds. J. Kołodziej, H. González-Vélez. Springer International Publishing, Cham. http://library.oapen.org/handle/20.500.12657/23334
- JOINER I.A. 2018. Artificial Intelligence. In: Emerging library technologies. It’s not just for geeks. Ed. I.A. Joiner. Elsevier, Amsterdam.
- KANE R. 2023. Adaptive acoustic walls – Robert Kane. Retrieved from https://cargocollective.com/kane/Adaptive-Acoustic-Walls
- KAZEEM K.O., OLAWUMI T.O., OSUNSANMI T. 2023. Roles of artificial intelligence and machine learning in enhancing construction processes and sustainable communities. Buildings, 13(8): 2061.
- KUMAR S., VERMA A.K., MIRZA A. 2024. Artificial intelligence-driven governance systems: smart cities and smart governance. In: Digital transformation, artificial intelligence and society. Frontiers of artificial intelligence, ethics and multidisciplinary applications. Springer, Singapore. https://doi.org/10.1007/978-981-97-5656-8_5
- LAM B., GAN W.S., SHI D.Y., NISHIMURA M., ELLIOTT S. 2021. Ten questions concerning active noise control in the built environment. Building and Environment, 200: 107928.
- LAURITSEN S.M., KRISTENSEN M., OLSEN M.V., LARSEN M.S., LAURITSEN M., JØRGENSEN M.J., LANGE J., THIESSON B. 2020. Explainable artificial intelligence model to predict acute critical illness from electronic health records. Nature Communications, 11(1): 1-11.
- LIU Y., MA X., SHU L., YANG Q., ZHANG Y., HUO Z., ZHOU Z. 2020. Internet of things for noise mapping in smart cities: State of the art and future directions. IEEE Network, 34(4): 112-118.
- LOPEZ-BALLESTER J., FELICI-CASTELL S., SEGURA-GARCIA J., COBOS M. 2023. AI-IoT Platform for blind estimation of room acoustic parameters based on deep neural networks. IEEE Internet of Things Journal, 10(1): 855-866.
- NOURANI V., GÖKÇEKUŞ H., UMAR I.K. 2020. Artificial intelligence based ensemble model for prediction of vehicular traffic noise. Environmental Research, 180: 108852.
- PAKNEJAD S.H., VADOOD M., SOLTANI P., GHANE M. 2021. Modeling the sound absorption behavior of carpets using artificial intelligence. The Journal of The Textile Institute, 112(11): 1763–1771.
- PAULINE S.H., SAMIAPPAN D., KUMAR R., ANAND A., KAR A. 2020. Variable tap-length non-parametric variable step-size NLMS adaptive filtering algorithm for acoustic echo cancellation. Applied Acoustics, 159: 107074.
- PEDRO C., LORDELO V. 2022. Deep learning methods for instrument separation and recognition. Queen Mary University of London Theses, London.
- PICINALI L.G., KATZ B.F., GERONAZZO M., MAJDAK P., REYES-LECUONA A., VINCIARELLI A., KATZ B.F. 2022. Artificial intelligence-driven immersive audio, from personalization to modeling. IEEE Signal Processing Magazine, 6.
- SEIBOLD M., MAURER S., HOCH A., ZINGG P., FARSHAD M., NAVAB N., FÜRNSTAHL P. 2021 Real-time acoustic sensing and artificial intelligence for error prevention in orthopedic surgery. Scientific Reports, 11(1): 1-11.
- SUSSKIND D., SUSSKIND R. 2018. The future of the professions. Proceedings of the American Philosophical Society, 162(2): 125-138.
- TAN J.K.A., LAU S.K. 2024. Experimental study of active noise control for a full-scale plenum window in a domestic apartment. Applied Acoustics, 224: 110120.
- TARAWNEH M., ALZYOUD F., SHARRAB Y. 2023. Artificial intelligence traffic analysis framework for smart cities. Computing Conference, London.
- TAYE M.M. 2023. Understanding of machine learning with deep learning: architectures, workflow, applications and future directions. Computers, 12(5): 91.
- VANKA S.S., SAFI M., ROLLAND J.-B., FAZEKAS G. 2023. Adoption of AI technology in the music mixing workflow: An investigation. Computer Science. Human-Computer Interaction. https://doi.org/10.48550/arXiv.2304.03407
- XU Y., LIU X., CAO X., HUANG C., LIU E., QIAN S., LIU X., WU Y., DONG F., QIU C.W., QIU J., HUA K., SU W., WU J., XU H., HAN Y., FU C., YIN Z., LIU M., ROEPMAN R., DIETMANN S., VIRTA M., KENGARA F., ZHANG Z., ZHANG L., ZHAO T., DAI J., YANG J., LAN L., LUO M., LIU Z., AN T., ZHANG B., HE X., CONG S., LIU X., ZHANG W., LEWIS J.P., TIEDJE J.M., WANG Q., AN Z., WANG F., ZHANG L., HUANG T., LU C., CAI Z., WANG F., ZHANG J. 2021. Artificial intelligence: A powerful paradigm for scientific research. The Innovation, 2(4): 100179. https://doi.org/10.1016/j.xinn.2021.100179
- YANG X. 2017. Adaptive Acoustic Origami. Melbourne School of Design, The University of Melbourne.
- ZHANG C., CHAONING C., ZHENG S., ZHANG M., QAMAR M., BAE S., KWEON I. 2023. A survey on audio diffusion models: Text to speech synthesis and enhancement in generative AI. https://doi.org/10.48550/arXiv.2303.13336
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Bibliografia
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bwmeta1.element.baztech-233e8407-b009-4c71-937c-686dd59a9eee