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99 results for “binaural”
Binaural room scanning files for sound field synthesis localization experiment
<p>Binaural room scanning files that were used together with the SoundScape Renderer to perform the localization experiments described in Wierstorf [1].</p> <p>The results of the corresponding listening experiments are summarized in Fig. 5.4, see https://github.com/hagenw/phd-thesis/tree/master/05_psychoacoustics/fig5_04</p> <p>[1] H. Wierstorf, Perceptual Assessment of Sound Field Synthesis, PhD dissertation, TU Berlin, 2014.</p>
Associated dataset for "Evaluation of Sensor Self-Noise in Binaural Rendering of Spherical Microphone Array Signals"
<p>The conducted instrumental and perceptual evaluation utilize the Real-Time Spherical Microphone Renderer (<a href="https://github.com/AppliedAcousticsChalmers/ReTiSAR">ReTiSAR</a>) for binaural reproduction in Python. However, the provided execution configurations (see below) are probably not exactly in accordance with the latest ReTiSAR code base. Hence, the at the time employed code state should be used in order to exactly reproduce the rendering results in this data set. The frozen code state for this data set is available at:<br> <a href="https://github.com/AppliedAcousticsChalmers/ReTiSAR/releases/tag/v2020.ICASSP">https://github.com/AppliedAcousticsChalmers/ReTiSAR/releases/tag/v2020.ICASSP</a></p> <p>Download the rendering pipeline and follow the setup instructions! Use the here included Conda environment file when setting up the Python environment. In this way you should obtain exactly the same Python setup as utilized in the instrumental and perceptual evaluation in the publication:</p> <pre><code>conda env create --file ReTiSAR_environment_freeze.yml</code></pre> <pre><code>source activate ReTiSAR_ICASSP_freeze</code></pre> <p>Directory "SNR":</p> <ul> <li>Tools for instrumental evaluation (Section 4)</li> <li>Shell script to capture input and output signals of rendering pipeline for sound field (target / wanted) and self-noise (unwanted) components for all specified configurations</li> <li>Matlab script to analyse captured signal and generate system transfer plots (Figure 1 to Figure 3 and further configurations)</li> </ul> <p>Directory "Relative Output Levels":</p> <ul> <li>Tools for preparation of perceptual evaluation (Section 5)</li> <li>Shell script to capture rendered uniformly contributing noise signals for all specified configurations</li> <li>Matlab script to analyse and level align captured signals and generate plot result plot (Figure 4)</li> </ul> <p>Directory "Absolute Output Levels":</p> <ul> <li>Tools for specification of perceptual evaluation (Section 5)</li> <li>Shell script to capture reproduced uniformly contributing noise signals for all specified configurations</li> <li>Matlab script to analyse the calibrated captured signals yielding the average level in the ear signals of 58.2 dBSPL (Section 5.1)</li> </ul> <p>Files in base directory and directory "Study Results":</p> <ul> <li>Tools for perceptual evaluation / user study (Section 5)</li> <li>Matlab GUI to conduct perceptual user study (employ by executing "ICASSP_gui.m", respective ReTiSAR instances are started and remote controlled by the GUI, raw study results will be stored in "results" directory)</li> <li>Matlab script to "calculate_conclusion.m" to analyse the raw study results and generate individual and conclusive result plots (Figure 5, Figure 6 and more)</li> </ul>
Hassan #1 binaural recording in Darb al-Ahmar, Cairo (Egypt), 25-10-2011
<p>« Mics in the Ears » binaural experiment in Cairo (Egypt): Vincent Battesti & Nicolas Puig, social anthropologists, asked inhabitants of Cairo megapolis in Egypt to record the surrounding urban sounds during one of their daily journeys (without the researcher), equipped with binaural microphones and GPS device. Participants have recorded in different Cairo neighbourhoods, and are themselves from different generations, social and economic backgrounds, and different genders.</p> <p>The two sound files are one the raw sound recorded by one of them during this walk in a neighbourhood in Cairo (see name of the inhabitant and date and place of recording in the file name), and the other the description and comments he or she gave us a posteriori when listening to this previous raw sound he or she recorded. See <a href="https://vbat.org/article831">https://vbat.org/article831</a></p>
Hassan #2 Route binaural recording in Duwiqa, Cairo (Egypt), 28-09-2012
<p>« Mics in the Ears » binaural experiment in Cairo (Egypt): Vincent Battesti & Nicolas Puig, social anthropologists, asked inhabitants of Cairo megapolis in Egypt to record the surrounding urban sounds during one of their daily journeys (without the researcher), equipped with binaural microphones and GPS device. Participants have recorded in different Cairo neighbourhoods, and are themselves from different generations, social and economic backgrounds, and different genders.</p> <p>The two sound files are one the raw sound recorded by one of them during this walk in a neighbourhood in Cairo (see name of the inhabitant and date and place of recording in the file name), and the other the description and comments he or she gave us a posteriori when listening to this previous raw sound he or she recorded. See <a href="https://vbat.org/article831">https://vbat.org/article831</a></p>
Salma binaural recording, Wast al-Balad, Cairo (Egypt), 26-09-2012
<p>« Mics in the Ears » binaural experiment in Cairo (Egypt): Vincent Battesti & Nicolas Puig, social anthropologists, asked inhabitants of Cairo megapolis in Egypt to record the surrounding urban sounds during one of their daily journeys (without the researcher), equipped with binaural microphones and GPS device. Participants have recorded in different Cairo neighbourhoods, and are themselves from different generations, social and economic backgrounds, and different genders.</p> <p>The two sound files are one the raw sound recorded by one of them during this walk in a neighbourhood in Cairo (see name of the inhabitant and date and place of recording in the file name), and the other the description and comments he or she gave us a posteriori when listening to this previous raw sound he or she recorded. See <a href="https://vbat.org/article831">https://vbat.org/article831</a></p>
Samir binaural recording in Bashtil, Cairo (Egypt), 28-09-2012
<p>« Mics in the Ears » binaural experiment in Cairo (Egypt): Vincent Battesti & Nicolas Puig, social anthropologists, asked inhabitants of Cairo megapolis in Egypt to record the surrounding urban sounds during one of their daily journeys (without the researcher), equipped with binaural microphones and GPS device. Participants have recorded in different Cairo neighbourhoods, and are themselves from different generations, social and economic backgrounds, and different genders.</p> <p>The two sound files are one the raw sound recorded by one of them during this walk in a neighbourhood in Cairo (see name of the inhabitant and date and place of recording in the file name), and the other the description and comments he or she gave us a posteriori when listening to this previous raw sound he or she recorded. See <a href="https://vbat.org/article831">https://vbat.org/article831</a></p>
Shady binaural recording in Wast al-Balad, Cairo (Egypt), 26-09-2012
<p>« Mics in the Ears » binaural experiment in Cairo (Egypt): Vincent Battesti & Nicolas Puig, social anthropologists, asked inhabitants of Cairo megapolis in Egypt to record the surrounding urban sounds during one of their daily journeys (without the researcher), equipped with binaural microphones and GPS device. Participants have recorded in different Cairo neighbourhoods, and are themselves from different generations, social and economic backgrounds, and different genders.</p> <p>The two sound files are one the raw sound recorded by one of them during this walk in a neighbourhood in Cairo (see name of the inhabitant and date and place of recording in the file name), and the other the description and comments he or she gave us a posteriori when listening to this previous raw sound he or she recorded. See <a href="https://vbat.org/article831">https://vbat.org/article831</a></p>
Binaural room impulse responses of an apartment-like environment
<p>Measured Binaural Room Impulse Responses (BRIR) of the ADREAM Laboratory, LAAS-CNRS, Toulouse, France. The measurements are described in detail in this publication:</p> <p>F. Winter, H. Wierstorf, A. Podlubne, T. Forgue, J. Manhès, M. Herrb, S. Spors, A. Raake, and P. Danès, "Database of binaural room impulse responses of an apartment-like environment," Proc. of 140th Aud. Eng. Soc. Conv., Paris, 2016</p> <p>Abstract of the Publication:</p> <p>We present a database of measured binaural room impulse responses (BRIRs) captured in an apartment-like environment. The BRIRs were measured for four different sound source positions, each combined with four listener positions with a head-orientation varying in the range of +-78° with 2° resolution. Additionally, BRIRs for 20 listener positions along a trajectory connecting two of the four positions were measured, each with a fixed head-orientation. The data is provided in the Spatially Oriented Format for Acoustics (SOFA) and it is freely available under Creative Commons (CC-BY-4.0). It can be used to simulate complex acoustic scenes in order to study the process of auditory scene analysis for humans and machines.</p>
Binaural room impulse responses recorded with KEMAR of a 19-channel linear loudspeaker array
<p>BRIRs for 19 different loudspeakers placed in room Calypso at the Telefunken-building of TU Berlin were measured. The room is a studio listening room. The 19 loudspeakers constituted a linear loudspeaker array with a inter-loudspeaker distance of roughly 15cm. The measurement was done with the KEMAR (type 45BA) with the corresponding large ears (type KB0065 and KB0066) and Fostex PM0.4 loudspeakers. The dummy head was rotated from −90° to 90° in 1° steps. The measurement was repeated with the head wearing AKG K601 open headphones.</p>
Binaural room impulse responses recorded with KEMAR in a mid-size lecture hall
<p>The binaural room impulse responses (BRIRs) were measured at the mid-size lecture room Auditorium 3 at the<br> Telefunken-building of TU Berlin. They were measured for six different loudspeaker positions. 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> </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>
Dataset for: Application of Machine Learning for the Spatial Analysis of Binaural Room Impulse Responses
<p>This repository contains supplementary material for the paper titled `Application of Machine Learning for the Spatial<br> Analysis of Binaural Room Impulse Responses' Available at: <a href="http://dx.doi.org/10.3390/app8010105">dx.doi.org/10.3390/app8010105</a> . These programs and audio files are distributed in the hopes that they will prove useful under the Creative Commons Attribution 4.0, with no warranty; or the implied warranty of merchantability or fitness for a particular problem. Please give appropriate credit for use of the material provided in this repository back to the author. </p> <p>In order to use the MatLab code the Auditory Toolbox by Malcolm Slaney [1] and the Cochleagram function distributed by Bin Gao [2] are required.</p> <p>The python scrips require the following Python libraries to be installed: Numpy[3], SciPy[4] and Tensorflow [5].</p> <p>The MatLab code was tested using MatLab R2017a on a Computer running windows 7.</p> <p>The python code was tested using Python 3.2.5, using an anaconda Python environment - in windows command line.</p> <p>--</p> <p>The repository contains:</p> <p>Folders:</p> <p><br> 1.) neg90 - This folder contains the gaussian normalisation parameters stored as text files and the weights and biases for the trained neural network - these are all for the -90° rotation neural network.</p> <p>2.) pos90 - This folder contains the gaussian normalisation parameters stored as text files and the weights and biases for the trained neural network - these are all for the +90° rotation neural network.</p> <p>3.) testData - this folder contains pre-generated test data for the different binaural dummy head microphones, speaker, and signal type combinations.</p> <p>Python Scripts:</p> <p><br> 1.) AnalyseDoA.py - A python script that can be run to test the neural network using the pre-generated test data - running the script will allow the user to input the binaural dummy head, speaker, and signal type. The important variables generated by this script are DoA - the direction of arrival for each signal in the feature vector, and yDiff - the difference between the predicted DoA and the expected direction of arrival</p> <p>2.) DirectionAnalysis.py - This python file contains a set of function that are used to define the neural network, and run it. The function called DoAPrediction takes the feature vector generated by the MatLab code as its input argument, these features will then be passed to the neural network, and the output of this function is the direction of arrival predicted by the neural network for each signal. The functions: DoAAnalysis_neg90 and DoAAnalysis_pos90 are called by the DoAPrediction function, these functions create the neural network using the NN function, import the weights and biases, and passes the feature matrix (provided as input) through the neural network - the output of these functions are the predicted direction of arrival.</p> <p>MatLab files:</p> <p><br> 1.) runAnalysis.m - This MatLab script analyses the dataset provided as part of this repository. Users can change the variables head ('KEMAR' or 'KU100'), signalType ('directSound' or 'reflection'), and speaker ('EquatorD5' or 'Genelec8030'). This script will produce the gaussian normalised feature vector and expected direction of arrival for all signals with the defined head, signal type, and speaker combination. These variables are then saved in .mat files so they can be imported by the python scripts.</p> <p>2.) BinauralModelCochlea.m - This MatLab function analyses a given binaural signal and outputs the interaural cross-correlation, interaural level difference, interaural time difference, the cochlea output for the left and right channel and the centre frequencies of the gammatone filter band. The input variables are: IR - the signal to be analysed, N - the number of gammatone filters, freqLow - the lowest centre frequency of the gammatone filter bank (centre frequency of the first gammatone filter), and freqHigh - the highest centre frequency of the gammatone filter bank (the centre frequency of the Nth gammatone filter). This function requires Malcolm Slaney's Auditory Toolbox [1] and Bin Gao's Cochleagram function [2] in order to work.</p> <p>3.) generateFeatureVector.m - This MatLab function generates a feature vector from an input binaural signal x, and a version of the signal captured after the binaural dummy head has been rotated by either +90° or -90° degree (variables xPos90 and xNeg90 respectively). If the sampling frequency (Fs) isn't 44100, the signals are resampled to be at 44100. This file also contains a function 'gaussianNormalisationTestData' which gaussian normalises the data using the mean and standard deviation calculated from the data used to train the neural networks - the mean and standard deviation values are stored in the folder GMParams in the pos90 and neg90 folders.</p> <p>4.) generateTestData.m - This MatLab function analyses the included binaural dataset, it takes the input variables: head - the binaural dummy head used for the measurements either 'KEMAR' or 'KU100', speaker - the speaker used for the measurements either 'EquatorD5' or 'Genelec8030', and signalType - the type of signal being analysed either 'directSound' or 'reflection'.</p> <p>Text files:</p> <p><br> 1.) noLayers.txt - a text file containing the number of layers used when training the neural network - with the current version of the code the neural network contains only 1 layer.</p> <p>2.) README.txt - Read me file containing information about the repository.</p> <p>Audio files:</p> <p><br> This repository contains 1152 binaural signals half of which are direct sounds segmented from a binaural room impulse responses and the other half are reflections segmented from binaural room impulse responses (detailed in the paper this material supports) the direct sounds are recorded at angles from 0° to 357.5° in steps of 2.5° and the reflections are recorded at angles of 1° to 358.5° in steps of 2.5°. In the paper only recordings relating to signals recorded with the Equator D5 are analysed.</p> <p>The combination of audio files include:</p> <p>1.) 144 direct sound recordings captured with the KEMAR 45BC binaural dummy head microphone and the Equator D5 speaker<br> 2.) 144 reflection recordings captured with the KEMAR 45BC binaural dummy head microphone and the Equator D5 speaker<br> 3.) 144 direct sound recordings captured with the KU100 binaural dummy head microphone and the Equator D5 speaker<br> 4.) 144 reflection recordings captured with the KU100 binaural dummy head microphone and the Equator D5 speaker<br> 5.) 144 direct sound recordings captured with the KEMAR 45BC binaural dummy head microphone and the Genelec 8030 speaker<br> 6.) 144 reflection recordings captured with the KEMAR 45BC binaural dummy head microphone and the Genelec 8030 speaker<br> 7.) 144 direct sound recordings captured with the KU100 binaural dummy head microphone and the Genelec 8030 speaker<br> 8.) 144 reflection recordings captured with the KU100 binaural dummy head microphone and the Genelec 8030 speaker</p> <p>The files are stored using the following file naming convention:<br> head_Test3_speaker_signalType_000_0_Degrees.wav - where _000_0 defines the azimuth direction of arrival so for example for a direct sound measured with the KEMAR unit and the Genelec8030 at 5 degrees would be 'KEMAR_Test3_Genelec8030_directSound_005_0Degrees.wav' and for a reflection measured with the KU100 and the Equator D5 at 298.5 degrees would be 'KU100_Test3_EquatorD5_reflection_298_5Degrees.wav'</p> <p>--</p> <p>Bibliography:<br> [1] Slaney, M. (1998). Auditory Toolbox. Palo Alto, CA. [Online]. Available: https://engineering.purdue.edu/~malcolm/interval/1998-010/ [Accessed: Oct. 27, 2017]</p> <p>[2] Gao, B. (2014). Cochleagram and IS-NMF2D for Blind Source Separation. [Online] Available: http://uk.mathworks.com/matlabcentral/fileexchange/48622-cochleagram-and-is-nmf2d-for-blind-source-separation?focused=3855900&tab=function [Accessed: Oct. 27, 2017]</p> <p>[3] NumFocus. (n.d.). NumPy. [Online]. Available: http://www.numpy.org/ [Accessed: Oct. 27, 2017]</p> <p>[4] SciPy. (n.d.). SciPy. [Online]. Available: https://www.scipy.org/ [Accessed: Oct. 27, 2017]</p> <p>[5] Google. (n.d.). TensorFlow. [Online] Available: https://www.tensorflow.org/ [Accessed: Oct. 27, 2017]</p> <p>--</p> <p>All code and audio produced by: Michael Lovedee-Turner, PhD candidate in Music Technology at the Audio Lab, Department of Electronic Engineering, University of York</p> <p>Contact: mjlt500@york.ac.uk</p>
BinauRec: A dataset to test the influence of the use of room impulse responses on binaural speech enhancement
<p>BinauRec is a dataset for binaural speech enhancement. It is composed of real recordings, measured and simulated room impulse responses for the same audio scenes. Measurements are realized using behind-the-ears hearing aid shells, with and without a dummy head.</p>
Extensive crowdsourced dataset of in-situ evaluated binaural soundscapes of private dwellings containing subjective sound-related and situational ratings along with person factors to study time-varying influences on sound perception — research data
<p><strong>Abstract:</strong></p> <p>The soundscape approach highlights the role of situational factors in sound evaluations; however, only a few studies have applied a multi‐domain approach including sound‐related, person‐related, and time‐varying situational variables. Therefore, we conducted a study based on the Experience Sampling Method to measure the relative contribution of a broad range of potentially relevant acoustic and non‐auditory variables in predicting indoor soundscape evaluations. Here we present the comprehensive dataset for which 105 participants reported temporally (rather) stable trait variables such as noise sensitivity, trait affect, and quality of life. They rated 6.594 situations regarding the soundscape standard dimensions, perceived loudness, and the saliency of its sound components and evaluated situational variables such as state affect, perceived control, activity, and location. To complement these subject‐centered data, we additionally crowdsourced object‐centered data by having participants make binaural measurements of each indoor soundscape at their homes using a low‐(self‐)noise recorder. These recordings were used to compute (psycho‐)acoustical indices such as the energetically averaged loudness level, the A‐weighted energetically averaged equivalent continuous sound pressure level, and the A‐weighted five‐percent exceedance level. This complex hierarchical data can be used to investigate time‐varying non‐auditory influences on sound perception and to develop soundscape indicators based on the binaural recordings to predict soundscape evaluations.</p> <p><strong>Content:</strong></p> <ul> <li><a href="https://zenodo.org/record/7858848/files/01%20StudyDescription.pdf">01 StudyDescription.pdf </a> <ul> <li>Description of the field study.</li> <li>Information about the methods and materials used.</li> </ul> </li> <li><a href="https://zenodo.org/record/7858848/files/02%20Dataset.csv">02 Dataset.csv</a> <ul> <li>The dataset, consisting of 93 variables describing 6594 observations taken by 105 participants.</li> </ul> </li> <li><a href="https://zenodo.org/record/7858848/files/03%20VariableDescriptions_EnglishPersonQuestionnaire.pdf">03 VariableDescriptions_EnglishPersonQuestionnaire.pdf</a> <ul> <li>Descriptions of all variables, their measurement scale, scale ranges and levels.</li> <li>Questions and task descriptions of the Experience Sampling Method questionnaire in German language with an English translation.</li> <li>English translations of questions asked in the person questionnaire.</li> </ul> </li> <li><a href="https://zenodo.org/record/7858848/files/04%20ESM-Questionnaire.pdf">04 ESM-Questionnaire.pdf</a> <ul> <li>Screenshots of the original Experience Sampling Method questionnaire with English translations.</li> </ul> </li> <li><a href="https://zenodo.org/record/7858848/files/05%20PersonQuestionnaire_OriginalGermanVersion.pdf">05 PersonQuestionnaire_OriginalGermanVersion.pdf</a> <ul> <li>Original version of the person questionnaire in German language.</li> </ul> </li> <li><a href="https://zenodo.org/record/7858848/files/06%20HelpTexts.pdf">06 HelpTexts.pdf</a> <ul> <li>Descriptions of the study task.</li> <li>Explanations of the scales used in the questionnaire.</li> <li>Explanations of the sound categories and the soundscape composition.</li> <li>Explanation of the operation of the recording device.</li> </ul> </li> <li><a href="https://zenodo.org/record/7858848/files/AcousticFeatures_README.md">AcousticFeatures_README.md</a> <a href="https://zenodo.org/api/files/3d784540-c0f4-412f-8742-df1db6f5401d/TimeSeries_and_Spectrograms_README.md?versionId=9291496c-d2c6-4151-96f1-a2ad99e1a540"> </a> <ul> <li>Descriptions of the structure of the AcousticFeatures_xxx.csv and .zip files.</li> <li>Analyis settings used in Artemis Suite to generate the acoustic features.</li> </ul> </li> <li><a href="https://zenodo.org/record/7858848/files/AcousticFeatures_SingleValues.csv">AcousticFeatures_SingleValues.csv</a> <ul> <li>All acoustic features, aggregated to single values per feature, recording, and channel.</li> </ul> </li> <li><a href="https://zenodo.org/record/7858848/files/AcousticFeatures_Spectra.csv">AcousticFeatures_Spectra.csv</a> <ul> <li>Time-averaged 1/3 octave spectra of each channel of each recording, A-weichted and un-weighted.</li> </ul> </li> <li><a href="https://zenodo.org/record/7858848/files/AcousticFeatures_Spectrograms.zip">AcousticFeatures_Spectrograms.zip</a> <ul> <li>13188 .csv files with un-weighted spetrograms of each channel of each recording.</li> </ul> </li> <li><a href="https://zenodo.org/record/7858848/files/AcousticFeatures_TimeSeries.zip">AcousticFeatures_TimeSeries.zip</a> <ul> <li>A .csv file containing LAeq and LZeq time series of each channel of each recording.</li> </ul> </li> </ul> <p><strong>Publications refering to this dataset:</strong></p> <p>Versümer, Siegbert; Steffens, Jochen; Weinzierl, Stefan (currently under review): "The role of loudness predictions, personal and situational factors in day-to-day loudness assessments of indoor soundscapes."</p> <p><strong>Funding:</strong></p> <p>This study was sponsored by the German Federal Ministry of Education and Research. “FHprofUnt” funding code: 13FH729IX6. </p> <p><strong>License: </strong></p> <p>CC 4.0 BY, <a href="https://creativecommons.org/licenses/by/4.0/legalcode">https://creativecommons.org/licenses/by/4.0/legalcode</a></p> <p><strong>Version history:</strong></p> <p>Details can be found in the <a href="https://zenodo.org/api/files/a15d6a91-1a35-4b5e-a7ec-da8a9bcbee2b/Changelog.md">Changelog.md</a> file.</p> <ul> <li> V.01.0. March 7, 2023: Initial publication. <a href="https://doi.org/10.5281/zenodo.7193938">https://doi.org/10.5281/zenodo.7193938</a></li> <li> V.01.1. April 25, 2023. <a href="https://doi.org/10.5281/zenodo.7858848">https://doi.org/10.5281/zenodo.7858848</a></li> </ul>
Binaural room impulse responses of a 5.0 surround setup for different listening positions
<p>Binaural Room Impulse Responses - KEMAR, room Calypso, TU Berlin, 5.0 Surround setup<br /> </p> <p>This dataset contains binaural room impulse responses (BRIRs) measured at nine<br /> different listening positions for a 5.0 surround setup in the listening room<br /> Calypso in the Telefunken building of Technische Universität Berlin, Berlin,<br /> Germany. The room has a volume of 83 m³ and a reverberation time RT60 of 0.17 s<br /> at a frequency of 1 kHz.</p> <p>"doc.zip" contains additional information for the measurement,<br /> "*.sofa" are the actual BRIRs, one file for every listening position, where the<br /> position is indicated by the X*-Y*-values.<br /> In order to work with those files you need a SOFA API for your programming<br /> language. For example, the one for Matlab can be found here:<br /> https://github.com/sofacoustics/API_MO/releases/latest<br /> If you want to create a single SOFA file containing all listening positions, you<br /> can execute the "combine_positions.m" script in Matlab after installing and<br /> starting the SOFA API.</p> <p>The BRIRs were with a head-orientation varying in the range of +-90° with 1°<br /> resolution. Room shape and size, listener and sound source positions are shown<br /> in "setup_calypso_surround_genelec8030A.pdf".</p> <p>Directory "./photos" contains photographs of the measurement setup.</p> <p>Copyright 2016 Hagen Wierstorf</p> <p>Licensed under Creative Commons (CC-BY-4.0)</p>
Binaural room scanning files for a 56-channel circular loudspeaker array
<p>Binaural room scanning (BRS) files for the simulation of a 56-channel circular loudspeaker array with a diameter of 3m. The loudspeaker array setup is also suited to reproduce stereo or surround recordings.</p> <p>The BRS files allow for a dynamic binaural simulation of the actual loudspeaker array using the SoundScape Renderer [1]. With this you can listen to binaural simulations of stereo, surround, or even wave field synthesis (WFS) productions. For example, you can find music productions that can be used with the 56-channel array at [2].</p> <p>[1] http://spatialaudio.net/ssr/</p> <p>[2] http://dx.doi.org/10.14279/depositonce-5173</p>
Binaural recordings of a real and binaural simulated circular loudspeaker array
<p>A KEMAR dummy head did binaural recordings of a noise signal played back over a circular loudspeaker array. The loudspeaker array had a diameter of 3m and consists of 56 loudspeakers. The real loudspeakers or a binaural simulation of them were used. For the latter a BRIR dataset had been recorded before with another dummy head. The KEMAR dummy head was wearing headphones all the time in order to allow for a direct comparison between the simulation and real setup.</p> <p>This dataset is used to create Fig. 4.9 in H. Wierstorf, Perceptual Assessment of of Sound Field Synthesis, PhD dissertation, TU Berlin, 2014. See also https://github.com/hagenw/phd-thesis/tree/master/04_binaural_synthesis/fig4_09</p>
Binaural room impulse responses of a 5.0 surround setup for different listening positions
<p>This dataset contains binaural room impulse responses (BRIRs) measured at nine<br> different listening positions for a 5.0 surround setup in the listening room<br> Calypso in the Telefunken building of Technische Universität Berlin, Berlin,<br> Germany. The room has a volume of 83 m³ and a reverberation time RT60 of 0.17 s<br> at a frequency of 1 kHz. The measurment was done with Genelec 8030A loudspeakers<br> and repeated for the central listening positon with the larger Genelec 8250A<br> loudspeakers.</p> <p>"doc.zip" contains additional information for the measurement,<br> "*.sofa" are the actual BRIRs, one file for every listening position, where the<br> position is indicated by the X*-Y*-values. The file<br> `KEMAR_Calypso_Surround.sofa` contains all listening positions in one file.<br> In order to work with those files you need a SOFA API for your programming<br> language. For example, the one for Matlab can be found here:<br> https://github.com/sofacoustics/API_MO/releases/latest</p> <p>The BRIRs were with a head-orientation varying in the range of +-90° with 1°<br> resolution. Room shape and size, listener and sound source positions are shown<br> in `setup_calypso_surround_genelec8030A.pdf` and <br> `setup_calypso_surround_genelec8250A.pdf`.</p> <p>Directory "./photos" contains photographs of the measurement setup.</p> <p>Copyright 2016 Hagen Wierstorf</p> <p>Licensed under Creative Commons (CC-BY-4.0)<br> </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: 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>
Localisation of a real vs. binaural simulated point source -- data
<p>This data set contains stimuli and results from an experiment that compared the localisation of a real point source realised by a loudspeaker to the localisation of a binaural simulation of the same source using head related impulse responses (HRIRs) or binaural room impulse responses (BRIRs). The results are published in [1].</p> <p>The corresponding binaural room scanning (BRS) files for the binaural simulation can be found in the file `brs.zip`, the employed noise stimulus in `stimuli.zip`. The file `results.zip` contains the results of all 11 listeners to the localisation task and the file `results_head_movements.zip` the recoreded head movements the listeners performed during the task. The file analysis.zip` contains average results and a plotting script.</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.