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89 results for “Impulse Response”
Dataset of impulse responses from variable acoustics room Arni at Aalto Acoustic Labs
<p>A dataset of impulse responses collected in the variable acoustics laboratory Arni at Acoustics Lab of Aalto University, Espoo, Finland.</p> <p>IRs of 5342 configurations of sound absorption in Arni are included in the dataset. Each of them were measured using an omnidirectional sound source and 5 sound receivers. For each configuration, 5 IRs were captured. The total number of measurements in the dataset is 132 037.</p> <p>For more information and the reverberation time values estimated from the IRs, please see the paper "Calibrating the Sabine and Eyring formulas" by Karolina Prawda, Sebastian J. Schlecht, and Vesa Välimäki, in The Journal of the Acoustical Society of America</p> <p>The work leading to producing the dataset and related research was supported by the Nordic Sound and Music Computing Network---NordicSMC, NordForsk project number 86892.</p> <p> </p> <p><strong>How to read the files in the dataset:</strong></p> <p>The general style of file naming is:<br> IR_numClosed_NumberOfReflectivePanels_numComb_CombinationNumber_mic_ReceiverNumber_sweep_SweepNumber<br> for example, for 1 reflective panel, combination 87, IR obtained from 3rd out of 5 sweeps recorded by microphone number 2, the filename is:<br> IR_numClosed_1_numComb_87_mic_2_sweep_3.wav</p> <p>The dataset was divided into several files due to its total size. The files included in each .zip file are indicated in its name.</p> <p>If some of the sound files are missing, e.g. for a certain combination and microphone there are 4 IR recordings instead of 5, it means that the sweep was discarded in the pre-processing phase due to non-stationary noise.<br> Read more: Karolina Prawda, Sebastian J. Schlecht, and Vesa Välimäki, "Robust selection of clean swept-sine measurements in non-stationary noise", The Journal of the Acoustical Society of America 151, 2117-2126 (2022), doi: https://doi.org/10.1121/10.0009915</p> <p>The specific combinations with indication whether the panel was in a reflective (represented by figure 0) or an absorptive (represented by figure 1) state are listed in <strong>combinations_setup.csv</strong> file.<br> The first column contains the combination number (0--5341), the first row is the panel number (1--55).</p> <p><strong>Arni_panels_numbers.pdf</strong> contains a diagram showing the panel numbers and locations.</p> <p><strong>Arni_layout.jpg</strong> contains a drawing specifying the positions of source source, sound receivers, and other elements of the interior.</p> <p> </p>
Modeling hydraulic heads with impulse response functions in different environmental settings (dataset and code supplement)
<p>These folders contain the input data, the scripts, and the output to reproduce the results and figures of Jemeljanova et al. "Modeling hydraulic heads with impulse response functions in different environmental settings".<br> </p> <p>This research is funded by the Latvian Council of Science, project “Spatial and temporal prediction of groundwater drought with mixed models for multilayer sedimentary basin under climate change”, project No. lzp-2019/1-0165 and PostDoc research project agreement No. 1.1.1.2/VIAA/3/19/524.</p>
Pilot Trial of Neural Correlates of Response to Treatment of PTSD-Associated Impulsive Aggression
ClinicalTrials.gov study NCT00333931. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Impulsivity and Alcohol Response
ClinicalTrials.gov study NCT03736343. IPD Sharing: NO. Countries: 1. Publications: 0.
Impulsivity Domains and Subjective Response
ClinicalTrials.gov study NCT05929677. IPD Sharing: NO. Countries: 1. Publications: 0.
GIR Dataset: A Geometry and real Impulse Response Dataset
<p>The GIR dataset is an open source dataset composed of more than 900k Impulse Responses (IRs). To foster the research in computational acoustics and in particular on the relationship between geometry and acoustic parameters, the measurements include acoustic responses acquired in 2952 positions and 312 surfaces. To maximize consistency, surfaces were 3D printed and the measurement process was automated using two robots. Detailed explanation of the dataset creation methods and possible applications are discussed in Rust <em>et al.</em> 2021 (<a href="https://doi.org/10.1177/1351010X20986901">https://doi.org/10.1177/1351010X20986901</a>) and Xydis <em>et al.</em> 2021 (in prep).</p> <p>The provenance and metadata tracked on Renku is enriched with the additional attributes recommended in the framework<a href="https://arxiv.org/abs/1805.03677"> dataset nutrition labels</a> and Schema.org note on<a href="https://schema.org/docs/data-and-datasets.html"> Data and Datasets</a>. This enriched metadata is provided in a standard JSON-LD format on Renku (<a href="https://renkulab.io/projects/ddad/gir-dataset/files/blob/dataset.json">dataset.json</a>) and on Zenodo as part of the published dataset (<a href="https://doi.org/10.5281/zenodo.5288744">https://doi.org/10.5281/zenodo.5288744</a>).</p> <p>Dataset is released under<a href="https://renkulab.io/projects/ddad/gir-dataset/files/blob/LICENSE"> the GNU General Public License v3.0</a></p>
Clinical Response of Impulsivity After Brain Stimulation in Parkinson's Disease
ClinicalTrials.gov study NCT04811807. IPD Sharing: NO. Countries: 0. Publications: 0.
Impulse Responses (IRs) of selected reverb processors with different settings
<p>The issues of reverberation in acoustic architecture and in music production share the same theoretical core, nevertheless the first one has been scientifically researched in depth while the second one remains at technical and experimental crossroads. It could be stated that the ISO 3382 parameters were proposed in the “analog” era for room acoustics (actual halls), whereas the “digital” parameters introduced in software, artificial reverbs, are not standardized in any way but help to create desired reverberation for music or audio effects. The interest herein is to bind these two disciplines together and analyze some of the significant descriptors of room acoustics (RT, C50, C80, BR, ER, CT, STI) applied in plug-in reverberant processors to observe how the virtual space is affected by changing the values of different parameters. Psychoacoustic ranges of JND were applied to conclude their relevance (or rather, influence), and whether it is possible to perceive alteration. Five of the selected, popular and commercial VST reverbs are juxtaposed with five similar settings and the results of analysis might be useful for sound mixers and automated mixing algorithms.The issues of reverberation in acoustic architecture and in music production share the same theoretical core, nevertheless the first one has been scientifically researched in depth while the second one remains at technical and experimental crossroads. It could be stated that the ISO 3382 parameters were proposed in the “analog” era for room acoustics (actual halls), whereas the “digital” parameters introduced in software, artificial reverbs, are not standardized in any way but help to create desired reverberation for music or audio effects. The interest herein is to bind these two disciplines together and analyze some of the significant descriptors of room acoustics (RT, C50, C80, BR, ER, CT) applied in plug-in reverberant processors to observe how the virtual space is affected by changing the values of different parameters. Psychoacoustic ranges of JND were applied to conclude their relevance (or rather, influence), and whether it is possible to perceive alteration. Five of the selected, popular and commercial VST reverbs are juxtaposed with five similar settings and the results of analysis might be useful for sound mixers and automated mixing algorithms.</p>
Impulse responses of selected reverb processors with different settings
<p>The issues of reverberation in acoustic architecture and in music production share the same theoretical core, nevertheless the first one has been scientifically researched in depth while the second one remains at technical and experimental crossroads. It could be stated that the ISO 3382 parameters were proposed in the “analog” era for room acoustics (actual halls), whereas the “digital” parameters introduced in software, artificial reverbs, are not standardized in any way but help to create desired reverberation for music or audio effects. The interest herein is to bind these two disciplines together and analyze some of the significant descriptors of room acoustics (RT, C50, C80, BR, ER, CT, STI) applied in plug-in reverberant processors to observe how the virtual space is affected by changing the values of different parameters. Psychoacoustic ranges of JND were applied to conclude their relevance (or rather, influence), and whether it is possible to perceive alteration. Five of the selected, popular and commercial VST reverbs are juxtaposed with five similar settings and the results of analysis might be useful for sound mixers and automated mixing algorithms.The issues of reverberation in acoustic architecture and in music production share the same theoretical core, nevertheless the first one has been scientifically researched in depth while the second one remains at technical and experimental crossroads. It could be stated that the ISO 3382 parameters were proposed in the “analog” era for room acoustics (actual halls), whereas the “digital” parameters introduced in software, artificial reverbs, are not standardized in any way but help to create desired reverberation for music or audio effects. The interest herein is to bind these two disciplines together and analyze some of the significant descriptors of room acoustics (RT, C50, C80, BR, ER, CT, STI) applied in plug-in reverberant processors to observe how the virtual space is affected by changing the values of different parameters. Psychoacoustic ranges of JND were applied to conclude their relevance (or rather, influence), and whether it is possible to perceive alteration. Five of the selected, popular and commercial VST reverbs are juxtaposed with five similar settings and the results of analysis might be useful for sound mixers and automated mixing algorithms.</p>
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