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89 results for “Impulse Response”
Binaural room impulse responses: Same listener-source-setup at different positions in the room
<p>To study the perception of room acoustics in dependency of the position in the room, measurements with KEMAR head-and-torso-simulator were conducted. The dummy head was placed at 5 different positions in a small conference room (10.3mx5.8mx3.1m, RT=0.65s). The source, a loudspeaker Genelec 1030A, was always positioned in the same relation to the listening position. BRIRs were measured with an azimuth-resolution of 5° from 0°-360°. This data allows a psychoacoustical comparison of the room acoustical properties at different positions in the room.</p>
Binaural room impulse responses: Same listener-source-setup at different positions in the room
<p>To study the perception of room acoustics in dependency of the position in the room, measurements with KEMAR head-and-torso-simulator were conducted. The dummy head was placed at 5 different positions in a small conference room (10.3mx5.8mx3.1m, RT=0.65s). The source, a loudspeaker Genelec 1030A, was always positioned in the same relation to the listening position. BRIRs were measured with an azimuth-resolution of 5° from 0°-360°. This data allows a psychoacoustical comparison of the room acoustical properties at different positions in the room.</p>
Binaural room impulse responses recorded with KEMAR in a small meeting room
<p>The binaural room impulse responses (BRIRs) were measured in the small meeting room Spirit at the<br> Telefunken-building of TU Berlin. They were measured for three different loudspeaker positions placed around a table. The head of the dummy head was rotated with a resolution of 1° ranging from -90° to 90°. The measurement equipment was the same as described in Wierstorf et al. [1]</p> <p>[1] Wierstorf, H., Geier, M., Raake, A., Spors, S. (2011) “A Free Database of Head-Related Impulse Response Measurements in the Horizontal Plane with Multiple Distances,” 130th AES Convention, eBrief 6</p>
MeshRIR: Dataset of Room Impulse Responses on Meshed Grid Points
<p>MeshRIR is a dataset of acoustic room impulse responses (RIRs) at finely meshed grid points. Two subdatasets are currently available: one consists of IRs in a 3D cuboidal region from a single source, and the other consists of IRs in a 2D square region from an array of 32 sources. This dataset is suitable for evaluating sound field analysis and synthesis methods. </p> <p>See the link below for the details:</p> <p><a href="https://sh01k.github.io/MeshRIR/">https://sh01k.github.io/MeshRIR/</a></p>
The impulse response of optic flow sensitive descending neurons to roll m-sequences
<p>When animals move through the world, their own movements generate widefield optic flow across their eyes. In insects, such widefield motion is encoded by optic lobe neurons. These lobula plate tangential cells (LPTCs) synapse with optic flow sensitive descending neurons, which in turn project to areas that control neck, wing and leg movements. As the descending neurons play a role in sensori-motor transformation, it is important to understand their spatio-temporal response properties. Recent work shows that a relatively fast and efficient way to quantify such response properties is to use m-sequences or other white noise techniques. We therefore here used m-sequences to quantify the impulse responses of optic flow sensitive descending neurons in male <i>Eristalis tenax </i>hoverflies. We focused on roll impulse responses as hoverflies perform exquisite head roll stabilizing reflexes, and the descending neurons respond particularly well to roll. We found that the roll impulse responses were fast, peaking after 16.5-18.0 ms. This is similar to the impulse response time-to-peak (18.3 ms) to widefield horizontal motion recorded in hoverfly LPTCs. We found that the roll impulse response amplitude scaled with the size of the stimulus impulse, and that its shape could be affected by the addition of constant velocity roll or lift. For example, the roll impulse response became faster and stronger with the addition of excitatory stimuli, and vice versa. We also found that the roll impulse response had a long return to baseline, which was significantly and substantially reduced by the addition of either roll or lift.</p>
MR Gradient System Long-Term Stability Investigation and Protocol Optimization for Quality Control using Gradient Impulse Response Function (GIRF)
<p>The dataset of the abstract "MR Gradient System Long-Term Stability Investigation and Protocol Optimization for Quality Control using Gradient Impulse Response Function (GIRF)" for ISMRM 2022, London, UK. The data processing code with instructions could be found <a href="https://github.com/BRAIN-TO/girfISMRM2022">here</a>.</p> <p> </p> <p>Meas1.zip and Meas2.zip contain the first and the second measurements of the raw T2* decay signal acquired with the phantom-based method. Note that the coil dimension has been averaged to save data volume for demonstration purposes. This will lead to a lower SNR of the calculated output gradient and GIRF.</p> <p> </p> <p>CalculatedGIRF.zip provides the author's pre-calculated GIRFs using the data without coil averaging. This data is used for all the postprocessing (e.g. SNR and stability analysis, etc.) in the published abstract with the source code provided in the same Github repository.</p> <p> </p>
A dataset of measured spatial room impulse responses in different rooms including visualization
<p>An open-source dataset of captured spatial room impulse responses (SRIRs) is presented. The<br> data was collected in different enclosed spaces at the Technische Universität Ilmenau using an open self-build<br> microphone array design following the spatial decomposition method (SDM) guidelines. The included rooms<br> were selected based on their distinctive acoustical properties resulting from their general build and furnishing as<br> required by their utility. Three different classes of spaces can be distinguished, including seminar rooms, offices,<br> and classrooms. For each considered space different source-receiver positions were recorded, including 360°<br> images for each condition. The dataset can be utilized for various augmented or virtual reality applications, using<br> either a loudspeaker or headphone-based reproduction alongside the appropriate head-related transfer function sets.<br> In future, we plan to add more rooms and more source-receiver positions.</p> <p>Please cite our corresponding paper:</p> <p>Klein, F., Surdu, T., Aretz, A., Birth, K., Edelmann, N., Seitelman, F., Ziener, C., Werner, S., and Sporer, T., “A dataset of measured spatial room impulse responses in different rooms including visualization,” in 152nd AES Convention, 2022, https://www.aes.org/e%E2%80%90lib/browse.cfm?elib=21728</p> <p> </p>
Binaural Impulse Response Dataset: Square Plate in Anechoic Chamber
<p><span>The dataset at hand contains impulse responses that have been measured along two discretized trajectories in the vicinity of a 25 mm thick 1 m x 1 m medium density fiberboard plate. Such data can serve as reference for the modelling of acoustic edge diffraction. This dataset was used in the context of research on binaural perception of diffracted sound in a publication that is in press at the Journal of the Acoustical Society of America</span></p>
Multi-Purpose Room Impulse Response Dataset Measured on a 3D Spatial Grid
<h1>Introduction</h1> <p>The sound field inside a room depends on many factors, such as the room shape, the absorption characteristics of the materials that comprise the bounding surfaces, the furniture present in the room, and the source position and its acoustic characteristics. An increasing number of publicly available room impulse response (RIR) databases that aim to provide detailed descriptions of interior sound fields can be found in the literature. These databases can be utilized in research as well as in the development and verification of signal processing algorithms that use this information on the acoustic environment. The availability of many RIR databases covering diverse scenarios is beneficial to the community.</p> <p>We provide a database of RIRs, namely the <strong>M</strong>ulti-<strong>P</strong>urpose <strong>RIR</strong> (<strong>MP-RIR</strong>) dataset, which contains 68736 RIRs measured on a dense 3D grid inside a complex-shaped room. We used a measurement robot with a rotating arm that operates as a linear guide and is capable of moving a vertical, linear array of eight omni-directional microphones. Four different sources have been used and were placed at eight different positions inside the room. A detailed desciption of the measurement campaign and the dataset is presented in the paper (https://aes2.org/publications/elibrary-page/?id=22515). </p> <h1>Contents of the MP-RIR dataset</h1> <p>In the following, the contents and the structure of the provided dataset are described:</p> <ul> <li>Sk_Mrir.npy:<br>Matrix, which contains the RIRs for all measured grid points for the loudspeaker Sk, k = 1, 2, ..., 8.<br>The matrix has the shape [N_xy, N_z, N] = [1074 x 8 x 100096], where N_xy is the number of 2D grid positions to which the robot is moving the vertical microphone array of N_z microphones. The length of each RIR is described by N.</li> <li>Mxyz.npy:<br>Matrix, which contains the microphone coordinates of the measured RIRs and corresponds to the matrices Sk_Mrir.<br>The matrix has the shape [N_xy, N_z, N_d] = [1074 x 8 x 3]. The indexing for the first two dimensions is the same as for the matrices Sk_Mrir, so that the microphone coordinates can be immediately retrieved for the provided RIRs. The third dimension with the length N_d gives access to the x-, y- and z-coordinate values in meters.</li> <li>Setup.npz<br>Dictionary, which contains parameters related to the measurement setup, with the following keys:<br> <ul> <li>angles_speaker<br>Dictionary of azimuth angles in degrees of the loudspeakers, with the keys S1, S2, ..., S8.</li> <li>coord_speaker_center<br>Dictionary, which contains the x-, y- and z-coordinates of the loudspeaker positions at the center of the base of each loudspeaker. The coordinate arrays can be accessed with the keys S1, S2, ..., S8.</li> <li>coord_polygon<br>Array of shape [4,2], which contains the x- and y-coordinates in meters of the room corners C_q, q=0,1,2,3.<br>The first dimension of the array relates to the room corners and the second dimension relates to the coordinates. </li> <li>fs<br>Sampling rate in Hz.</li> <li>T_guard<br>Guard time in samples. The guard time provides additional samples at the beginning of the RIR to increase the quality of the RIR.</li> <li>T_system<br>Delay of the measurement system in samples.</li> </ul> </li> </ul> <h1>Further Information</h1> <p>The delay of the RIRs is composed of the guard time T_guard, the system delay T_system and the acoustic delay T_ac. The guard time and system delay can be retrieved from the file Setup.npz described above.</p> <p>A gain alignment procedure was applied to align the output SPL between the loudspeakers, as described in the paper. Additionally, all RIRs were scaled by the same value, the maximum absolute peak of all measured RIRs. As a result, the maximum absolute value in each individual RIR is less or equal to 1.</p>
Room Impulse Responses for Low-Frequency Sound Field Control
<h2>About</h2> <div> <div> <div> <p>A dataset of room impulse responses (RIRs) measured in the low frequency range, for different measurement signal lengths, in two rooms with different acoustic conditions. Acquired with the purpose of low-frequency sound zones rendering and evaluation, the dataset can be used in general for different sound field control methods.</p> <p>By design, the dataset is composed of two sets of RIRs: one intended for the design of the control strategies, and another one intended for evaluation [1]. The RIRs of the first set, obtained with measurement signals of different length, allow exploring the influence of the acquisition time of the RIRs in the control methods [2]. The RIRs of the second set allow evaluating the sound field generated at and around the position of the RIRs of the first set.</p> <p>The RIRs were acquired with the Synchronized Swept-Sine (SSS) method, proposed by Novak et al. [3], at a samplig frequency of 48 kHz with SSS signals varying from 15 Hz to 600 Hz. The obtained RIRs were re-sampled to 1.2 kHz.</p> <p>Two files with different contents have been added:</p> <ul> <li><strong>RIR_LF_SFC_Light:</strong> contains the documentation, MatLab codes, and the ready-to-use RIRs stored as 3D-arrays in .mat files.<br><br></li> <li><strong>RIR_LF_SFC_Full:</strong> in addition to files in <strong>RIR_LF_SFC_Light</strong>, it contains the original SSS signals and the signals recorded during the measurements. These were used to retrieve the RIRs and therefore, can be used for custom purposes. <br><br></li> </ul> </div> </div> </div> <div> <h2>Citation</h2> <p>Please cite the database with the following paper:</p> <p>@inproceedings{cadavid_ATvsSS_2024,<br>title={Spatial Sampling versus Acquisition Time of Room Impulse<br> Responses for Low-Frequency Sound Zones},<br> author={Cadavid, Jos{\'e} and M{\o}ller, Martin Bo and van Waterschoot, Toon and Bech, S{\o}ren and {\O}stergaard, Jan},<br> booktitle={Audio Engineering Society Convention 156},<br> year={2024},<br> organization={Audio Engineering Society} }</p> <h2>Acknowledgements</h2> <p>The authors would like to thank <a href="https://orcid.org/0000-0002-1452-2227" target="_blank" rel="noopener">Antonin Novak</a>, <a href="https://orcid.org/0000-0002-2175-6603" target="_blank" rel="noopener">Christian S. Pedersen</a>, and Claus Vestergaard for their help with the RIRs measurements.</p> <p>This project has received funding from the European Union’s (EU) Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie Actions Grant No. 956369.</p> </div>
Room Impulse Response measurements of a rectangular room
<p>This archive contains the data for a Gitlab hosted project (https://github.com/epfl-lts2/joint_estimation_of_room_geometry_and_modes). This archive allows users to extract the Room impulse responses (RIRs) measurements for a real rectangular room. A total of 132 measurements are included. Furthermore, users have the option to perform several post processing steps on the RIRs such as filtering, downsampling and truncation in time domain. Please refer to the guidelines pdf for more information.</p>
Ambisonic Room Impulse Responses
<p>Datasets of Ambisonic room impulse responses from 3 european museums/touristic sites:</p> <ul> <li>La Fundació Miro, Barcelona, Spain</li> <li>Die Alte Pinakotheke, Munich, Germany</li> <li>St Andrews Castle, St Andrews, Scotland</li> </ul> <p>The datasets are in SOFA format of convention AmbisonicsDRIR, recently proposed by the author.</p>
Model of Sant Climent de Taüll: Impulse Responses and Auralisations.
<p>One of the most emblematic Romanesque paintings of La Vall de Boí, Catalonia, is the Pantocrator, a fresco found at Sant Climent de Taüll. However, only a small part of the church paintings is preserved whereas at the time of its construction, in 1123, its walls and columns were fully covered. If the church has experienced a complete transformation of its wall materials during the last 900 years, it can be assumed that its acoustic properties have also changed. This paper aims to recreate this acoustic transformation by building a computer model, analysing the acoustic effect of such paintings, and comparing three auralisation examples. The model is created using ODEON Geometric Acoustic Software, and calibrated using Impulse Responses taken in the real church. The results suggest that the paintings change the acoustics of the church, adding more than a second of reverb time, even with the relatively small dimensions of the church. This also affects speech intelligibility and music clarity.</p>
Sweet Area Impulse Response Database
<p>A dataset of acoustic impulse responses measured in the Immersive Media Lab (https://www.ikt.uni-hannover.de/de/institut/ausstattung/immersive-media-lab) listening room at the Institute of Communications Technology.</p> <p>Measurements were taken using a Neumann KU 100 dummy head and an mh acoustics em32 Eigenmike microphone array. The arrays were mounted on a robot arm and acoustic impulse responses in a spatial grid around the loudspeaker setup's sweet spot were measured using the ITA toolbox (https://www.ita-toolbox.org/). The setup consists of 42 loudspeakers.</p> <p>Version 1.0 of the dataset uses a custom Matlab struct format relying on itaAudio objects for storing the data. Conversion to the standardized SOFA format is planned.</p> <p>Details on the measurement setup are given in:</p> <blockquote> <p>Roman Kiyan, Stephan Preihs, Jürgen Peissig, “Robokopp: Robotic Setup for Automated Sweet Spot Measurements with Head Simulators and Microphone Arrays,” in Fortschritte der Akustik - DAGA 2024 (http://pub.dega-akustik.de/DAGA_2024/konferenz?article=614)</p> </blockquote> <p>The dataset is the basis of the analyses of the following papers:</p> <blockquote> <p>Roman Kiyan, Stephan Preihs, Jürgen Peissig, “Determining the immersion sweet area in multichannel loudspeaker reproduction using spatial sound field features,” presented at the Audio Engineering Society Convention 156 (http://aes2.org/publications/elibrary-page/?id=22520)</p> </blockquote> <blockquote> <p>Roman Kiyan, Stephan Preihs, Jürgen Peissig, “Signal dependencies of the immersion sweet area in multichannel loudspeaker reproduction,” TBA.</p> </blockquote>
Spatial Room Impulse Response Dataset: A Robot's Journey Through Coupled Rooms of a Reverberant University Building
<p>This is a dataset of Spatial Room Impulse Responses obtained by a robot equipped with a microphone array.</p> <p>The measurements were conducted in a reverberant university building, the <em>Helmholtz</em> building at<em> Technische Universität Ilmenau</em> (coordinates: N50.6815788133375°, E10.939294371903342°). All the floors in the building are covered with bare stone tiles, the walls are not acoustically treated. Only the hallway has a suspended acoustic ceiling. The file "Pictures Overview.jpg" shows some impressions of the building. Note that the floorplan only shows parts of the building that were connected to the measurement area by open doors.</p> <p>The area covered by the robot is in a hallway on the top floor (2nd floor starting with ground floor) with two stairwells at both ends. To specifically study the behavior of coupled rooms and occluded sources, the sound sources were placed in adjacent sections of the building and on multiple floors. See the file "Measurement Overview.jpg" for an overview of the source positions and the receiver areas covered. Areas 2 and 3 were captured with a higher spatial resolution than area 1 to analyze the transition between the hallway and the staircases. The receiver positions form a uniform grid, the pitch between positions is shown in the following table. Due to time and technical constraints, only a maximum of 3 sources were used per run, so there are not all combinations of sources and receiver areas. Refer to the following table to see which source was active for which area and which zip file contains the according data:</p> <table> <tbody> <tr> <th>Filename</th> <th>Sources</th> <th>Receiver Area</th> <th>Receiver Positions [ct]</th> <th>Pitch [cm]</th> </tr> </tbody> <tbody> <tr> <td>Helmholtzbau_OG2_HM_HS.zip</td> <td>HM, HS</td> <td>Area 1</td> <td>143</td> <td>50</td> </tr> <tr> <td>Helmholtzbau_OG2_SML_SSL_SSU.zip</td> <td>SML, SSL, SSU</td> <td>Area 1</td> <td>154</td> <td>50</td> </tr> <tr> <td>Helmholtzbau_OG2_SMU_SML_HM.zip</td> <td>SMU, SML, HM</td> <td>Area 2</td> <td>88</td> <td>25</td> </tr> <tr> <td>Helmholtzbau_OG2_SSU_SSL_HS.zip</td> <td>SSU, SSL, HS</td> <td>Area 3</td> <td>92</td> <td>25</td> </tr> </tbody> </table> <p>As an example "Plot Reverberation Time.jpg" shows the reverberation times for all measured positions of Area 1 and 2 with speaker HM.</p>
OTIMP: The Oticon-Imperial hearing aid impulse response database
<p>A database of acoustic impulse responses measured between a sphere of loudspeakers and hearing aids in a mildly reverberant listening room. The database includes measurements on 46 individuals and is particularly intended to allow the evaluation of hearing aid algorithms when applied to devices worn by different individuals.</p> <p> </p> <p>Version history</p> <p>1.0.0 Original</p> <p>1.0.1 Re-uploaded as individual zip files - No change to the actual data but allows the most commonly used segment(s) of the data to be downloaded more conveniently.</p>
A High-Resolution Spatial Room Impulse Response Database
<p><strong>A High-Resolution Spatial Room Impulse Response Database:</strong></p> <p>A Database of various SRIRs measured in three rooms, for two receiver and 3 source positions each. The positions are shown in the floor plans. </p> <p><strong>Naming Convention:</strong></p> <p><strong>Receivers</strong>: SMA (DRIRs): spherical microphone array impulse responses on a 2702 sampling point Lebedev grid.</p> <p> KU100 (BRIRs): Neumann KU100 dummy head impulse responses on a 360 sampling point horizontal grid</p> <p> Omni_ir: Omnidirectional impulse responses measured with an Earthworks M30 microphone </p> <p><strong>Receiver positions:</strong> P1, P2 as indicated in the floor plans</p> <p><strong>Source positions:</strong> LSL: left speaker, LSR: right speaker, LSC: center speaker as indicated in the floor plans </p> <p><strong>Rooms: </strong>Audiolab, Classroom, Audimax</p> <p>_______________________________________________________________________________________</p> <p><strong>Contact:</strong><br> Tim Lübeck, Johannes M. Arend, and Christoph Pörschmann<br> TH Köln - University of Applied Sciences<br> Institute of Communications Engineering<br> Department of Acoustics and Audio Signal Processing<br> Betzdorfer Str. 2, D-50679 Cologne, Germany</p> <p><a href="https://www.th-koeln.de/personen/tim.luebeck/">https://www.th-koeln.de/personen/tim.luebeck/</a></p> <p><a href="https://www.th-koeln.de/personen/johannes.arend/">https://www.th-koeln.de/personen/johannes.arend/</a></p> <p><a href="http://www.th-koeln.de/personen/christoph.poerschmann/">https://www.th-koeln.de/personen/christoph.poerschmann/</a><br> <br> </p>
Multi-Angle, Multi-Distance Microphone Impulse Response Dataset
<p>This archive contains data generated as part of the PhD research of Juan Carlos Franco, investigating the timbral attributes related to the incident-angle-dependent response of microphones. </p> <p>The dataset of microphone impulse responses (IRs) comprises 25 microphones, including a Class-1 measurement microphone, covering the polar pattern variations of 7 of the microphones. The measurements were performed following a quasi-anechoic method, at incident angles from 0° to 355° with an angular resolution of 5°, and at source-to-microphone distances of 0.5 m, 1.25 m and 5m. </p> <p>Both normalised (-1 dBFS peak) and raw versions of the IRs have been rendered at bit-depths of 24-bit and 32-bit, with a sample rate of 48 kHz. </p> <p>A detailed description of the measurement procedure, as well as the equipment used, is provided in the associated journal paper [Franco et al. 2021].</p> <p><strong>References</strong></p> <p>J Franco, B Bǎcilǎ, T Brookes, E De Sena, "A multi-angle, multi-distance dataset of microphone impulse responses", J.Aud.Eng.Soc., Volume 70, Issue 10 pp. 882-893, October 2022, doi 10.17743/jaes.2022.0027</p>
6 DoF Directional Room Impulse Response Dataset Measured over a Dense Loudspeaker Grid (6DRIR-DL)
<p>The 6DoF directional RIR dataset (aka <strong>6DRIR-DL</strong>) includes room impulse responses (RIRs) measured by <strong>nine</strong> spherical microphone arrays (SMAs; Zylia ZM-1S) distributed in a semi-cuboid room. <strong>6DRIR-DL</strong> is specialized by its massive loudspeaker positions (<strong>392</strong> locations), which were incorporated for the 6DOF source localization task. The inter-element spacing between loudspeakers is only 8 cm, so the dataset can be utilized to validate a sound source localization algorithm for closely positioned multiple sound sources.</p>
ASN Database - v3.2 - Database of Simulated Room Impulse Responses for Acoustic Sensor Networks Deployed in Complex Multi-Source Acoustic Environments
<p>We present a large set of simulated room impulse responses for a multi-room apartment. The simulated apartment models a real vacation apartment for which a recorded set of audio data has already been made available in the context of the DCASE challenges. The impulse responses were rendered using a dense grid of sources and receivers by means of a hybrid auralization algorithm based on a low-order image-source method and deterministic cone tracing. The proposed data set can be used to generate a wide variety of acoustic scenes which, in turn, can benefit numerous data-demanding machine-learning algorithms.<br> <br> To obtain more information on the database, please visit <a href="https://github.com/Jearde/asn-database">the website</a>.<br> <strong>Please read the license file (available in the GitHub repository) before using the database.</strong></p>
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.