GIR dataset: A geometry and real impulse response dataset for machine learning research in acoustics

Cox, 2016 Blauert, 1997 Olive SE, Toole FE, The detection of reflections in typical rooms, in: Audio Engineering Society Convention 85, Audio Engineering Society, 1988. Siltanen S, Lokki T, Savioja L, Rays or waves? understanding the strengths and weaknesses of computational room acoustics modeling techniques, in: Proc. Int. Symposium on Room Acoustics, 2010. Savioja, 2015, Overview of geometrical room acoustic modeling techniques, J Acoust Soc Am, 138, 708, 10.1121/1.4926438 Brinkmann, 2019, A round robin on room acoustical simulation and auralization, J Acoust Soc Am, 145, 2746, 10.1121/1.5096178 Badino, 2020, Acoustic Performance-Based Design: A Brief Overview of the Opportunities and Limits in Current Practice, Acoustics, 2, 246, 10.3390/acoustics2020016 Voulodimos, 2018, Deep learning for computer vision: A brief review, Comput Intell Neurosci, 10.1155/2018/7068349 Arulkumaran, 2017, Deep reinforcement learning: A brief survey, IEEE Signal Process Mag, 34, 26, 10.1109/MSP.2017.2743240 Niu H, Gong Z, Ozanich E, Gerstoft P, Wang H, Li Z, Deep learning for ocean acoustic source localization using one sensor, arXiv preprint arXiv:1903.12319. He K, Zhang X, Ren S, Sun J, Deep residual learning for image recognition, in: Proceedings of the IEEE conference on computer vision and pattern recognition, 2016, pp. 770–778. Wang, 2018, Underwater acoustic source localization using generalized regression neural network, J Acoust Soc Am, 143, 2321, 10.1121/1.5032311 Bianco, 2019, Machine learning in acoustics: Theory and applications, J Acoust Soc Am, 146, 3590, 10.1121/1.5133944 Mirvis SE, Garbage in, garbage out (How purportedly great ML models can be screwed up by bad data), Appl Radiol 31 (2) (2002) 5, iSBN: 0036-861X. doi:10.1037/e475262008-002. Nene SA, Nayar SK, Murase H, Columbia object image library (coil-20), Tech. Rep. CUCS-005-96, Department of Computer Science, Columbia University (February 1996). Xydis A, Perraudin N, Rust R, Heutschi K, Casas G, Riba Grognuz O, et al., GIR Dataset: A Geometry and real Impulse Response Dataset, type: dataset (Aug. 2021). doi:10.5281/zenodo.5500519. URL: www.zenodo.org/record/5500519. Jeub, 2009, A binaural room impulse response database for the evaluation of dereverberation algorithms, 1 Szöke, 2019, Building and evaluation of a real room impulse response dataset, IEEE J Selected Topics Signal Process, 13, 863, 10.1109/JSTSP.2019.2917582 Nakamura S, Hiyane K, Asano F, Nishiura T, Yamada T, Acoustical sound database in real environments for sound scene understanding and hands-free speech recognition, in: Proceedings of the Second International Conference on Language Resources and Evaluation (LREC’00), European Language Resources Association (ELRA), Athens, Greece, 2000. http://www.lrec-conf.org/proceedings/lrec2000/pdf/356.pdf. Eaton J, Gaubitch ND, Moore AH, Naylor PA, Acoustic characterization of environments (ace) challenge results technical report, arXiv preprint arXiv:1606.03365. Ravanelli, 2015, The dirha-english corpus and related tasks for distant-speech recognition in domestic environments, 275 Kendrick, 2006, Room acoustic parameter extraction from music signals, Vol. 5 Gamper, 2018, Blind reverberation time estimation using a convolutional neural network, 136 Shabtai, 2010, Room volume classification from reverberant speech Genovese, 2019, Blind room volume estimation from single-channel noisy speech, 231 Peters N, Lei H, Friedland G, Name that room: Room identification using acoustic features in a recording, in: Proceedings of the 20th ACM international conference on Multimedia, 2012, pp. 841–844. Papayiannis, 2020, End-to-end classification of reverberant rooms using dnns, IEEE/ACM Trans Audio, Speech, Language Process, 28, 3010, 10.1109/TASLP.2020.3033628 O’Donovan, 2008, Imaging concert hall acoustics using visual and audio cameras, 5284 Vanwynsberghe, 2015, Design and implementation of a multi-octave-band audio camera for realtime diagnosis, Appl Acoust, 89, 281, 10.1016/j.apacoust.2014.10.009 O’Donovan, 2007, Real time capture of audio images and their use with video, 10 O’Donovan, 2007, Microphone arrays as generalized cameras for integrated audio visual processing, 1 Antonacci, 2010, Geometric reconstruction of the environment from its response to multiple acoustic emissions, 2822 Lindell DB, Wetzstein G, Koltun V, Acoustic non-line-of-sight imaging, in: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2019, pp. 6780–6789. Lindell, 2019, Wave-based non-line-of-sight imaging using fast fk migration, ACM Trans Graphics (TOG), 38, 1, 10.1145/3306346.3322937 Crocco, 2016, Audio surveillance: A systematic review, ACM Comput Surveys (CSUR), 48, 1, 10.1145/2871183 Haubrick, 2019, Robust audio sensing with multi-sound classification, 1 Cobos, 2017, A survey of sound source localization methods in wireless acoustic sensor networks, Wireless Commun Mobile Computing ISO, ISO 17497–2 Acoustics - Sound-scattering properties of surfaces - Part 2: Measurement of the directional diffusion coefficient in a free field, iSBN: 0471297836 (2012). Bronstein MM, Bruna J, Cohen T, Veličković P, Geometric deep learning: Grids, groups, graphs, geodesics, and gauges, arXiv preprint arXiv:2104.13478. Mei S, Misiakiewicz T, Montanari A, Learning with invariances in random features and kernel models, in: Proceedings of Thirty Fourth Conference on Learning Theory, PMLR, 2021, pp. 3351–3418, iSSN: 2640–3498. URL: https://proceedings.mlr.press/v134/mei21a.html. Bietti A, Venturi L, Bruna J, On the sample complexity of learning with geometric stability, arXiv preprint arXiv:2106.07148. Xydis A, Du C, Rust R, Gramazio F, Kohler M, Visualization methods for big and high-dimensional acoustic data, in: ACADIA 2022: Hybrids & Haecceities [Proceedings of the 42st Annual Conference of the Association of Computer Aided Design in Architecture (ACADIA)], ACADIA, CUMINCAD, 2022. Accepted for publication. Rust, 2021, A data acquisition setup for data driven acoustic design, Build Acoust, 10.1177/1351010X20986901 Xydis A, Perraudin N, Rust R, Lytle BA, Gramazio F, Kohler M, Data-Driven Acoustic Design of Diffuse Soundfields, in: ACADIA 2021: Realignments: Toward Critical Computation [Proceedings of the 41st Annual Conference of the Association of Computer Aided Design in Architecture (ACADIA) pp. 170–181, ISBN 979-8-986-08056-7], ACADIA, CUMINCAD, 2021. URL: http://papers.cumincad.org/cgi-bin/works/paper/acadia21_170. Heddle J, Fresnel Zones and Spheroids for Room Acoustics (November) (2016) 1–10. Kingma DP, Ba J, Adam: A method for stochastic optimization, arXiv preprint arXiv:1412.6980. Achenbach, 2004, 55 Samarasinghe, 2017, Acoustic reciprocity: An extension to spherical harmonics domain, J Acoust Soc Am, 142, EL337, 10.1121/1.5002078 Rust R, Xydis A, Frick C, Strauss J, Junk C, Feringa J, Gramazio F, M. Kohler, Computational Design and Evaluation of Acoustic Diffusion Panels for the Immersive Design Lab, in: Towards a new, configurable architecture - Proceedings of the 39th eCAADe Conference, Vol. 1, 2021, p. 10.