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46 results for “RIR”
Dataset: Eigenmike-DRIRs, KEMAR 45BA-BRIRs, RIRs and 360° pictures captured at five positions of a small conference room
<p>A data set was created to study the position dependent perception of room acoustics in case of a small conference room. Binaural room impulse responses (BRIRs) were measured with KEMAR 45BA at 5 different potential listening positions. To keep the direct sound similar the Genelec 1030A two-way loudspeaker was always placed at a distance of 2.5m. In one condition, the loudspeaker was turned towards the listening position, in the other condition it was turned by 180° to achieve an indirect reproduction with low direct sound energy. Furthermore, an mh acoustics Eigenmike was placed at each of the five listening positions and 32-channel directional room impulses responses (DRIRs) as well as an omnidirectional room impulse response (RIR) were captured where the center of the head was placed before.</p> <p>Additionally, 360° visual footages were captured with a GoPro Omni spherical camera array to provide audiovisual impressions of the listening situation at the five positions. </p>
Kinect RIR
<p>Room impulse responses to simulate a CHiME-5 like dataset.</p> <p>Note: CHiME-5 dataset is recorded using Microsoft Kinect</p>
Room Impulse Responses (RIRs) for B-format recordings
<p>Room Impulse Responses (RIRs) for B-format recordings.</p> <p>This dataset in .mat format has been utilized for generating the reverberant speech mixtures for my recent work named "Exploiting Angular and Spectral Features for B-Format Speech Separation with Deep Neural Networks".</p>
HOMULA-RIR: A Room Impulse Response Dataset for Teleconferencing and Spatial Audio Applications Acquired Through Higher-Order Microphones and Uniform Linear Microphone Arrays
<p>In this paper, we present HOMULA-RIR, a dataset of room impulse responses (RIRs) acquired using both higher-order microphones (HOMs) and a uniform linear array (ULA), in order to model a remote attendance teleconferencing scenario. Specifically, measurements were performed in a seminar room, where a 64-microphone ULA was used as a multichannel audio acquisition system in the proximity of the speakers, while HOMs were used to model 25 attendees actually present in the seminar room. The HOMs cover a wide area of the room, making the dataset suitable also for applications of virtual acoustics. Through the measurement of the reverberation time and clarity index, and sample applications such as source localization and separation we demonstrate the effectiveness of the HOMULA-RIR dataset.</p>
R-Prox RIR samples Darmstadt June 2017
<p>This dataset contains Room Impulse Response (RIR) measurements that we collected for evaluating the R-Prox proximity verification system. The package contains the original RIR sample recordings, processed audio files after deconvolution with the original signal, further processed audio files where the parts exceeding the RIR have been cropped, and precomputed features in CSV files. All the audio files are 16bit mono PCM Wave files.<br> <br> The original.wav file is the generated excitation signal that was emitted in the rooms.<br> Other files follow the naming convention recorded_ROOM_RECORDER-ID_TIMESTAMP{_fullrir|_cutrir}.wav<br> The files where .wav follows directly the timestamp are the original recordings; the ones with <em>fullrir</em> in the name are the original recording after deconvolution with original.wav; the ones with <em>cutrir</em> in their name are the cropped RIR samples.</p> <p>The CSV files contain extracted features like the RT60 value for the entire signal and for specific frequency ranges. An example of the extracted features of a single sample:</p> <pre><code>Filter Band RT60 EDT D/R C10 C35 C50 C80 0.566 0.401 9.544 -0.590 5.064 7.300 11.096 Oct 125Hz 0.093 1.195 9.548 -9.351 -4.757 -2.745 -1.001 Oct 250Hz 0.430 3.367 9.552 -11.705 -8.236 -6.218 -4.841 Oct 500Hz 0.692 0.809 9.564 -3.952 -0.989 0.377 4.227 Oct 1kHz 0.640 0.582 9.559 -1.836 1.438 3.581 7.143 Oct 2kHz 0.636 0.484 9.543 -0.357 3.971 5.744 9.415 Oct 4kHz 0.589 0.370 9.549 0.451 6.333 8.095 11.789 Oct 8kHz 0.518 0.398 9.545 -1.018 4.701 7.201 11.088 Oct 16kHz 0.471 0.318 9.548 -1.463 5.970 8.914 13.408 1/3 125Hz 0.042 0.415 9.605 -2.504 -0.749 0.129 22.719 1/3 160Hz 0.122 0.633 9.573 -2.150 3.079 4.293 4.603 1/3 200Hz 0.274 2.361 9.545 -13.815 -9.676 -8.875 -6.187 1/3 250Hz 0.156 2.175 9.554 -9.833 -6.198 -5.467 -5.086 1/3 315Hz 0.046 0.572 9.557 -4.743 -2.653 3.075 7.797 1/3 400Hz 0.184 0.859 9.545 -6.032 -0.763 3.208 4.707 1/3 500Hz 0.688 0.976 9.555 -4.107 -0.176 1.401 2.865 1/3 630Hz 0.664 0.805 9.558 -6.423 -2.636 -1.604 3.992 1/3 800Hz 0.672 0.771 9.546 -3.799 -1.284 0.163 4.211 1/3 1kHz 0.620 0.644 9.546 -3.718 -0.355 0.606 4.326 1/3 1.3kHz 0.632 0.566 9.551 -3.745 0.293 3.464 8.282 1/3 1.6kHz 0.704 0.520 9.550 -1.082 3.188 5.015 7.854 1/3 2kHz 0.643 0.518 9.554 -0.331 2.060 5.214 8.615 1/3 2.5kHz 0.643 0.516 9.568 -1.302 4.395 5.647 8.990 1/3 3.2kHz 0.589 0.456 9.546 0.773 4.569 5.872 10.156 1/3 4kHz 0.586 0.351 9.549 -0.148 7.023 8.817 12.605 1/3 5kHz 0.603 0.435 9.545 -0.709 5.325 7.042 10.348 1/3 6.3kHz 0.567 0.385 9.546 -2.436 4.609 6.797 11.164 1/3 8kHz 0.502 0.414 9.545 -0.812 4.478 7.015 10.773 1/3 10kHz 0.438 0.328 9.554 -1.899 5.855 8.598 13.376 1/3 12.5kHz 0.321 0.237 9.598 -1.060 8.030 12.542 17.905 1/3 16kHz 0.541 0.341 9.546 0.635 6.372 8.562 11.948 1/3 20kHz 0.539 0.205 9.587 1.624 9.700 11.512 13.696</code></pre> <p> </p>
RIR samples Darmstadt and Helsinki, Summer-Autumn 2018
<p>This dataset contains Room Impulse Response (RIR) measurements that we collected for evaluating the DoubleEcho proximity verification system. The package contains the original RIR sample recordings, processed audio files after deconvolution with the original signal and cropping the RIR, and precomputed features in CSV files. All the audio files are 16bit mono PCM Wave files.<br> <br> The original.wav file is the generated excitation signal that was emitted in the rooms.<br> Other files follow the naming convention recorded_ROOM_emitter_EMITTER-ID_RECORDER-ID_TIMESTAMP{_cutrir}.wav<br> The files where .wav follows directly the timestamp are the original recordings; the ones with <em>cutrir</em> in their name are the cropped RIR samples.</p> <p>The CSV files contain extracted features like the RT60 value for the entire signal and for specific frequency ranges. An example of the extracted features of a single sample:</p> <pre><code>Filter Band RT60 EDT D/R C10 C35 C50 C80 0.566 0.401 9.544 -0.590 5.064 7.300 11.096 Oct 125Hz 0.093 1.195 9.548 -9.351 -4.757 -2.745 -1.001 Oct 250Hz 0.430 3.367 9.552 -11.705 -8.236 -6.218 -4.841 Oct 500Hz 0.692 0.809 9.564 -3.952 -0.989 0.377 4.227 Oct 1kHz 0.640 0.582 9.559 -1.836 1.438 3.581 7.143 Oct 2kHz 0.636 0.484 9.543 -0.357 3.971 5.744 9.415 Oct 4kHz 0.589 0.370 9.549 0.451 6.333 8.095 11.789 Oct 8kHz 0.518 0.398 9.545 -1.018 4.701 7.201 11.088 Oct 16kHz 0.471 0.318 9.548 -1.463 5.970 8.914 13.408 1/3 125Hz 0.042 0.415 9.605 -2.504 -0.749 0.129 22.719 1/3 160Hz 0.122 0.633 9.573 -2.150 3.079 4.293 4.603 1/3 200Hz 0.274 2.361 9.545 -13.815 -9.676 -8.875 -6.187 1/3 250Hz 0.156 2.175 9.554 -9.833 -6.198 -5.467 -5.086 1/3 315Hz 0.046 0.572 9.557 -4.743 -2.653 3.075 7.797 1/3 400Hz 0.184 0.859 9.545 -6.032 -0.763 3.208 4.707 1/3 500Hz 0.688 0.976 9.555 -4.107 -0.176 1.401 2.865 1/3 630Hz 0.664 0.805 9.558 -6.423 -2.636 -1.604 3.992 1/3 800Hz 0.672 0.771 9.546 -3.799 -1.284 0.163 4.211 1/3 1kHz 0.620 0.644 9.546 -3.718 -0.355 0.606 4.326 1/3 1.3kHz 0.632 0.566 9.551 -3.745 0.293 3.464 8.282 1/3 1.6kHz 0.704 0.520 9.550 -1.082 3.188 5.015 7.854 1/3 2kHz 0.643 0.518 9.554 -0.331 2.060 5.214 8.615 1/3 2.5kHz 0.643 0.516 9.568 -1.302 4.395 5.647 8.990 1/3 3.2kHz 0.589 0.456 9.546 0.773 4.569 5.872 10.156 1/3 4kHz 0.586 0.351 9.549 -0.148 7.023 8.817 12.605 1/3 5kHz 0.603 0.435 9.545 -0.709 5.325 7.042 10.348 1/3 6.3kHz 0.567 0.385 9.546 -2.436 4.609 6.797 11.164 1/3 8kHz 0.502 0.414 9.545 -0.812 4.478 7.015 10.773 1/3 10kHz 0.438 0.328 9.554 -1.899 5.855 8.598 13.376 1/3 12.5kHz 0.321 0.237 9.598 -1.060 8.030 12.542 17.905 1/3 16kHz 0.541 0.341 9.546 0.635 6.372 8.562 11.948 1/3 20kHz 0.539 0.205 9.587 1.624 9.700 11.512 13.696</code></pre>
Comparison of Safety and Efficiency of 20w 30w Holmium Laser Device in Treatment of 1-2 cm Diameter Kidney Stones With RIRS
ClinicalTrials.gov study NCT02451319. IPD Sharing: Not stated. Countries: 1. Publications: 1.
RIRS With Flex Suction Sheath vs. PCNL for 2-3 cm Renal Stones
ClinicalTrials.gov study NCT07058402. IPD Sharing: NO. Countries: 1. Publications: 1.
Clinical Efficacy of Mini-PCNLversus RIRS for the Management of Upper Urinary Tract Calculus (1-2.5 cm)
ClinicalTrials.gov study NCT06031103. IPD Sharing: NO. Countries: 1. Publications: 3.
RIRS for Treatment of Stones in Congenital Anomalous Kidneys
ClinicalTrials.gov study NCT05240170. IPD Sharing: Not stated. Countries: 1. Publications: 0.
RIR and the Impact on Clinical Outcomes in Patients Undergoing PCI
ClinicalTrials.gov study NCT05131750. IPD Sharing: Not stated. Countries: 1. Publications: 3.
SMP vs RIRS for Symptomatic Lower Pole Renal Calculi of 10-20 mm Size: a Randomized Controlled Trial
ClinicalTrials.gov study NCT02519634. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Effect of Ureteral Access Sheath Use on Postoperative Pain Level in Patients Undergoing RIRS
ClinicalTrials.gov study NCT02501525. IPD Sharing: NO. Countries: 1. Publications: 8.
RIRS Versus ESWL for the Treatment of Renal Stones
ClinicalTrials.gov study NCT02645058. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Mini-PNL, RIRS, and ESWL for Treatment of Medium-Sized, High-Density, Non-Lower Pole, Renal Stones
ClinicalTrials.gov study NCT04856722. IPD Sharing: NO. Countries: 1. Publications: 1.
Comparison of RIRS Versus PCNL Methods, According to Postoperative Pain and Analgesic Demand in 2 to 4 cm Renal Stones
ClinicalTrials.gov study NCT02430168. IPD Sharing: Not stated. Countries: 1. Publications: 2.
A Novel Method for Retrograde Intrarenal Surgery (RIRS)
ClinicalTrials.gov study NCT05202158. IPD Sharing: NO. Countries: 1. Publications: 2.
Effects of Education Given to RIRS With Mobile Application on Anxiety, Fear of Surgery, Pain, Analgesic Consumption, Length of Hospital Stay, Complication Development, Readmission and Hospitalization
ClinicalTrials.gov study NCT06812884. IPD Sharing: NO. Countries: 1. Publications: 1.
Differences in Urine NGAL Levels in Patients Undergoing RIRS With or Without Ureteral Access Sheath
ClinicalTrials.gov study NCT02485002. IPD Sharing: NO. Countries: 1. Publications: 6.
Retrograde Intrarenal Surgery (RIRS) With High-Power Laser and Flexible, Navigable Suction Access Sheath (FANS) vs Mini-Percutaneous Nephrolithotomy (miniPCNL) for 2-3 cm Renal Stones
ClinicalTrials.gov study NCT07349992. IPD Sharing: YES. Countries: 1. Publications: 0.
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.