├── get_homula-rir.sh ├── get_openair.sh ├── get_mit.sh ├── get_but.sh ├── get_mird.sh ├── get_c4dm.sh ├── get_rwcp_reverb_air.sh ├── get_gtu_rir.sh ├── get_miracle.sh ├── get_soundcam.sh ├── get_all_rirs.sh ├── get_sriracha.sh └── README.md /get_homula-rir.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | 3 | dest=$1 4 | 5 | wget -P $dest https://zenodo.org/records/10479726/files/HOMULA-RIR.zip 6 | unzip -q $dest/HOMULA-RIR.zip -d $dest 7 | -------------------------------------------------------------------------------- /get_openair.sh: -------------------------------------------------------------------------------- 1 | dest=$1 2 | 3 | wget -P $dest -q -nH -A wav -m -p -E -k -K -np -c -X */*/*/examples,*/*/*/images,*/*/*/'Data Tables' https://webfiles.york.ac.uk/OPENAIR/IRs/ 4 | -------------------------------------------------------------------------------- /get_mit.sh: -------------------------------------------------------------------------------- 1 | dest=$1 2 | 3 | wget -P $dest https://mcdermottlab.mit.edu/Reverb/IRMAudio/Audio.zip 4 | unzip -q $dest/Audio.zip -d $dest 5 | mv $dest/Audio $dest/MIT_Survey 6 | 7 | -------------------------------------------------------------------------------- /get_but.sh: -------------------------------------------------------------------------------- 1 | dest=$1 2 | 3 | wget -P $dest http://merlin.fit.vutbr.cz/ReverbDB/BUT_ReverbDB_rel_19_06_RIR-Only.tgz 4 | mkdir -p $dest/BUT_ReverbDB && tar -xf $dest/BUT_ReverbDB_rel_19_06_RIR-Only.tgz --directory $dest/BUT_ReverbDB 5 | 6 | -------------------------------------------------------------------------------- /get_mird.sh: -------------------------------------------------------------------------------- 1 | dest=$1 2 | 3 | wget -P $dest -q -r -np -nH https://www.eng.biu.ac.il/~gannot/RIR_DATABASE/ 4 | mv $dest/~gannot $dest/MIRD 5 | for z in $dest/MIRD/RIR_DATABASE/Impulse*.zip 6 | do 7 | unzip -q $z -d $dest/MIRD/RIR_DATABASE/ 8 | done 9 | -------------------------------------------------------------------------------- /get_c4dm.sh: -------------------------------------------------------------------------------- 1 | dest=$1 2 | 3 | for room in greathallOmni octagonOmni classroomOmni 4 | do 5 | mkdir -p $dest/C4DM/$room && wget -P $dest/C4DM/$room http://isophonics.net/files/irs/$room.zip 6 | unzip -q $dest/C4DM/$room/$room.zip -d $dest/C4DM/$room/ 7 | done 8 | 9 | -------------------------------------------------------------------------------- /get_rwcp_reverb_air.sh: -------------------------------------------------------------------------------- 1 | dest=$1 2 | 3 | # Thanks to authors of the paper "A Study on Data Augmentation of Reverberant Speech for Robust Speech Recognition" who have collected and processed the 3 datasets together 4 | wget -P $dest https://www.openslr.org/resources/28/rirs_noises.zip 5 | unzip -q $dest/rirs_noises.zip -d $dest 6 | 7 | -------------------------------------------------------------------------------- /get_gtu_rir.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | 3 | wget -O RIR.pickle.dat "https://gtu-my.sharepoint.com/:u:/g/personal/mpekmezci_gtu_edu_tr/Ec9dwMtiymlOuu_NSv5yT0YBeLwiFk8lwdhBpWrSCtPcZg?e=Xu50ok&download=1" 4 | mkdir -p gtu-rir 5 | mv RIR.pickle.dat gtu-rir 6 | cd gtu-rir 7 | wget https://raw.githubusercontent.com/mehmetpekmezci/gtu-rir/refs/heads/master/02.data/data_reader/read_data.py 8 | wget -O read_example.sh https://raw.githubusercontent.com/mehmetpekmezci/gtu-rir/refs/heads/master/02.data/data_reader/run.sh 9 | -------------------------------------------------------------------------------- /get_miracle.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | 3 | dest=$1 4 | 5 | if [ "$dest" == "" ]; then 6 | echo "Usage: $0 " 7 | exit 8 | fi 9 | 10 | 11 | mkdir -p $dest 12 | 13 | echo "Downloading A1.h5..." 14 | wget --content-disposition -O $dest/A1.h5 https://depositonce.tu-berlin.de/bitstreams/67156d9c-224d-4d07-b923-be0240e7b48d/download 15 | echo "Downloading A2.h5..." 16 | wget --content-disposition -O $dest/A2.h5 https://depositonce.tu-berlin.de/bitstreams/cbb462d7-cb28-4803-98d8-84b03aad0d5f/download 17 | echo "Downloading D1.h5..." 18 | wget --content-disposition -O $dest/D1.h5 https://depositonce.tu-berlin.de/bitstreams/86680ee5-ae0c-4b38-8ef8-805652a21ded/download 19 | echo "Downloading R2.h5..." 20 | wget --content-disposition -O $dest/R2.h5 https://depositonce.tu-berlin.de/bitstreams/0fc5f5a4-a2f7-4eb7-b796-7114260e5e86/download 21 | echo "Downloading loudspeaker.h5..." 22 | wget --content-disposition -O $dest/loudspeaker.h5 https://depositonce.tu-berlin.de/bitstreams/f16367cb-14cc-44f9-bb0b-9be3c33183d3/download 23 | -------------------------------------------------------------------------------- /get_soundcam.sh: -------------------------------------------------------------------------------- 1 | wget https://stacks.stanford.edu/file/druid:xq364hd5023/3Dscans.tar.gz 2 | wget https://stacks.stanford.edu/file/druid:xq364hd5023/ConferenceRoom_preprocessed.tar.gz 3 | wget https://stacks.stanford.edu/file/druid:xq364hd5023/ConferenceRoom_raw.tar.gz 4 | wget https://stacks.stanford.edu/file/druid:xq364hd5023/LivingRoom_preprocessed.tar.gz 5 | wget https://stacks.stanford.edu/file/druid:xq364hd5023/LivingRoom_raw.tar.gz 6 | wget https://stacks.stanford.edu/file/druid:xq364hd5023/TreatedRoom_preprocessed.tar.gz 7 | wget https://stacks.stanford.edu/file/druid:xq364hd5023/TreatedRoom_raw.tar.gz 8 | wget https://stacks.stanford.edu/file/druid:xq364hd5023/TreatedRoomPanels_preprocessed.tar.gz 9 | wget https://stacks.stanford.edu/file/druid:xq364hd5023/TreatedRoomPanels_raw.tar.gz 10 | tar –xf 3Dscans.tar.gz 11 | tar –xf ConferenceRoom_preprocessed.tar.gz 12 | tar –xf ConferenceRoom_raw.tar.gz 13 | tar –xf LivingRoom_preprocessed.tar.gz 14 | tar –xf LivingRoom_raw.tar.gz 15 | tar –xf TreatedRoom_preprocessed.tar.gz 16 | tar –xf TreatedRoom_raw.tar.gz 17 | tar –xf TreatedRoomPanels_preprocessed.tar.gz 18 | tar –xf TreatedRoomPanels_raw.tar.gz 19 | -------------------------------------------------------------------------------- /get_all_rirs.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | if [ "$1" == "" ]; then 3 | echo "Usage: $0 " 4 | exit 5 | fi 6 | 7 | dest=$(echo $1 | sed 's:/*$::') 8 | cleandir=true 9 | export PATH=$(pwd):$PATH 10 | 11 | if [ ! -d $dest/OPENAIR ]; then 12 | echo "Downloading OpenAIR dataset..." 13 | get_openair.sh $dest 14 | echo "Download finished." 15 | fi 16 | 17 | if [ ! -d $dest/RWCP_REVERB_AACHEN ]; then 18 | echo "Downloading RWCP, REVERB and Aachen datasets..." 19 | get_rwcp_reverb_air.sh $dest 20 | mv $dest/RIRS_NOISES $dest/RWCP_REVERB_AACHEN 21 | if $cleandir; then 22 | echo "Removing non-RIR files" 23 | pushd $dest/RWCP_REVERB_AACHEN 24 | rm -rf pointsource_noises simulated_rirs real_rirs_isotropic_noises/*noise* 25 | popd 26 | fi 27 | echo "Download finished." 28 | fi 29 | 30 | if [ ! -d $dest/BUT_ReverbDB ]; then 31 | echo "Downloading BUT Reverb Database..." 32 | get_but.sh $dest 33 | if $cleandir; then 34 | echo "Removing non-RIR files" 35 | find $dest/BUT_ReverbDB -type f -not -name '*IR*.wav' -delete # Delete non-RIR files 36 | find $dest/BUT_ReverbDB -name '*v0[1-9].wav' -delete # Delete repeated recordings 37 | fi 38 | echo "Download finished." 39 | fi 40 | 41 | if [ ! -d $dest/MIT_Survey ]; then 42 | echo "Downloading MIT Survey dataset..." 43 | get_mit.sh $dest 44 | echo "Download finished." 45 | fi 46 | 47 | if [ ! -d $dest/C4DM ]; then 48 | echo "Downloading C4DM Survey dataset..." 49 | get_c4dm.sh $dest 50 | echo "Download finished." 51 | fi 52 | 53 | #TODO: MIRD dataset comes in .mat file and needs to be converted 54 | if false && [ ! -d $dest/MIRD ]; then 55 | echo "Downloading MIRD dataset..." 56 | get_mird.sh $dest 57 | echo "Download finished." 58 | fi 59 | 60 | if [ ! -d $dest/MIRACLE ]; then 61 | echo "Downloading MIRACLE dataset..." 62 | get_miracle.sh $dest/MIRACLE 63 | echo "Download finished." 64 | fi 65 | 66 | if [ ! -d $dest/gtu-rir ]; then 67 | echo "Downloading GTU-RIR dataset..." 68 | get_gtu_rir.sh 69 | mv gtu-rir $dest/gtu-rir 70 | echo "Download finished." 71 | fi 72 | 73 | if [ ! -d $dest/HOMULA-RIR ]; then 74 | echo "Downloading HOMULA-RIR dataset..." 75 | get_homula-rir.sh $dest 76 | echo "Download finished." 77 | fi 78 | -------------------------------------------------------------------------------- /get_sriracha.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | 3 | dest=$1 4 | 5 | if [ "$dest" == "" ]; then 6 | echo "Usage: $0 " 7 | exit 8 | fi 9 | 10 | 11 | mkdir -p $dest 12 | 13 | echo "Downloading SR1-C1.h5..." 14 | wget --content-disposition -O $dest/SR1-C1.h5 https://depositonce.tu-berlin.de/bitstreams/75b3da38-9f7f-4b30-8967-3da1b0f29e9f/download 15 | echo "Downloading SR1-C2.h5..." 16 | wget --content-disposition -O $dest/SR1-C2.h5 https://depositonce.tu-berlin.de/bitstreams/8651dc9d-ec9c-4504-b301-7b5536fb74f3/download 17 | echo "Downloading SR1-C3.h5..." 18 | wget --content-disposition -O $dest/SR1-C3.h5 https://depositonce.tu-berlin.de/bitstreams/7c840fc0-90d5-40c1-8528-356b808560c8/download 19 | echo "Downloading SR1-C4.h5..." 20 | wget --content-disposition -O $dest/SR1-C4.h5 https://depositonce.tu-berlin.de/bitstreams/5bbf3409-205e-451b-abda-c16e90004f2a/download 21 | echo "Downloading SR1-D.h5..." 22 | wget --content-disposition -O $dest/SR1-D.h5 https://depositonce.tu-berlin.de/bitstreams/412b04ec-6852-417f-ab85-3e847133860e/download 23 | echo "Downloading SR2-C1.h5..." 24 | wget --content-disposition -O $dest/SR2-C1.h5 https://depositonce.tu-berlin.de/bitstreams/bff1df6c-2672-4352-aa80-34bb2aa7dfd1/download 25 | echo "Downloading SR2-C2.h5..." 26 | wget --content-disposition -O $dest/SR2-C2.h5 https://depositonce.tu-berlin.de/bitstreams/12e6d24a-5d55-415c-b461-fa10d850c63c/download 27 | echo "Downloading SR2-C3.h5..." 28 | wget --content-disposition -O $dest/SR2-C3.h5 https://depositonce.tu-berlin.de/bitstreams/b64c3d35-c337-4003-859d-e747bdbe2a3f/download 29 | echo "Downloading SR2-C4.h5..." 30 | wget --content-disposition -O $dest/SR2-C4.h5 https://depositonce.tu-berlin.de/bitstreams/272bd891-3463-4459-be03-9a66aa916841/download 31 | echo "Downloading SR2-D.h5..." 32 | wget --content-disposition -O $dest/SR2-D.h5 https://depositonce.tu-berlin.de/bitstreams/ec51a7e5-818d-463c-8f77-342c3bde27d8/download 33 | echo "Downloading SRA1-C1.h5..." 34 | wget --content-disposition -O $dest/SRA1-C1.h5 https://depositonce.tu-berlin.de/bitstreams/bfbda52e-4776-4499-a52f-92c01dd0f632/download 35 | echo "Downloading SRA1-C2.h5..." 36 | wget --content-disposition -O $dest/SRA1-C2.h5 https://depositonce.tu-berlin.de/bitstreams/f67da2d7-5c57-4ddc-8230-3f275563c497/download 37 | echo "Downloading SRA1-C3.h5..." 38 | wget --content-disposition -O $dest/SRA1-C3.h5 https://depositonce.tu-berlin.de/bitstreams/ff5cb621-402d-43a6-8ff8-bbbd8d8ae170/download 39 | echo "Downloading SRA1-C4.h5..." 40 | wget --content-disposition -O $dest/SRA1-C4.h5 https://depositonce.tu-berlin.de/bitstreams/24c0f12b-dbdd-4c23-8825-6657ed7249e4/download 41 | echo "Downloading SRA1-D.h5..." 42 | wget --content-disposition -O $dest/SRA1-D.h5 https://depositonce.tu-berlin.de/bitstreams/7950399f-e1be-4067-b672-b1c2b255a33b/download 43 | echo "Downloading SRA2-C1.h5..." 44 | wget --content-disposition -O $dest/SRA2-C1.h5 https://depositonce.tu-berlin.de/bitstreams/aa9d52fd-e7eb-4f38-93d8-e22733c8311f/download 45 | echo "Downloading SRA2-C2.h5..." 46 | wget --content-disposition -O $dest/SRA2-C2.h5 https://depositonce.tu-berlin.de/bitstreams/acb8baf0-7442-4faf-895d-7862004ffadc/download 47 | echo "Downloading SRA2-C3.h5..." 48 | wget --content-disposition -O $dest/SRA2-C3.h5 https://depositonce.tu-berlin.de/bitstreams/7351f03d-243b-4c52-97da-b9b45cdce6d4/download 49 | echo "Downloading SRA2-C4.h5..." 50 | wget --content-disposition -O $dest/SRA2-C4.h5 https://depositonce.tu-berlin.de/bitstreams/8b33b41b-51ca-44f6-a6b9-dac887d0dc7e/download 51 | echo "Downloading SRA2-D.h5..." 52 | wget --content-disposition -O $dest/SRA2-D.h5 https://depositonce.tu-berlin.de/bitstreams/61016fe8-96fe-463d-9441-d4c39b0a9898/download 53 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # room-impulse-responses 2 | A list of publicly available acoustic/room impulse response (AIR/RIR) datasets. Currently this repo only tracks real-world recorded room impulse responses. Datasets included here may contain other data (e.g., speech, noise) in addition to RIRs. But this repo only describes the datasets about their RIR contents below. While there may be other webpages (if not outdated) that list some of the RIR datasets, this repo provides a brief description about the content of each dataset so you don't have to download and inspect them one by one before realizing it is not what you desire. 3 | 4 | This repo also provides some scripts for downloading datasets if possible. Some dataset may require registration to download, which we may not provide download links directly. Only rows marked with a :heavy_check_mark: are directly downloadable by running `./get_all_rirs.sh [destination folder]`. 5 | 6 | For getting spatial RIRs in ambisonic format (i.e., `.sofa`), please refer to [another dedicated website](https://www.sofaconventions.org/mediawiki/index.php/SOFA_(Spatially_Oriented_Format_for_Acoustics)). 7 | 8 | | Name | Content | Year | Paper/Document | In script | 9 | | :----------------- | :------------- | :----- | :----- | :-----: | 10 | | [FLAIR](https://zenodo.org/records/17037517) | Contains a total of 270 room impulse responses in a single room, along with a millimeter accurate dense 3D point cloud of the room geometry and microphone positions. This dataset provides a basis for investigating inverse spatial audio problems that rely on boundary information. | 2025 | [Bayesian Sound Field Reconstruction Using Partial Boundary Information](https://ieeexplore.ieee.org/document/11197648) | 11 | | [SRIRACHA](https://depositonce.tu-berlin.de/items/d9d4b747-2f3e-4b21-b32e-48863e9af876) | The SRIRACHA dataset comprises room impulse responses of spatially distributed sources within a plane parallel to a planar microphone array measured in a shoebox room with changing absorption. It consists of 2,654,720 single-channel room impulse responses divided into eight different scenarios. A combination of two source-receiver plane distances, two different source arrangements, and two different absorption levels of the shoebox room was measured. The dataset is intended to serve as a benchmark for data-driven modelling and interpolation methods for room impulse responses. | 2025 | [SRIRACHA: Shoebox Room Impulse Response Archive with Varying Absorption](https://api-depositonce.tu-berlin.de/server/api/core/bitstreams/643a8b38-bc2e-43cb-89e8-f972ed4457f8/content) | :heavy_check_mark: 12 | | [HOMULA-RIR](https://github.com/polimi-ispl/homula-rir) | HOMULA-RIR is 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 (Eventide-Polimi eStick) was used as a multichannel audio acquisition system in the proximity of 2 speakers (Genelec 8020), while HOMs (Voyage Audio Spatial Mic) were used to model 25 attendees actually present in the seminar room. | 2024 | [HOMULA-RIR: A Room Impulse Response Dataset for Teleconferencing and Spatial Audio Applications Acquired through Higher-Order Microphones and Uniform Linear Microphone Arrays](https://doi.org/https://doi.org/10.1109/ICASSPW62465.2024.10626753) | :heavy_check_mark: 13 | | [GTU-RIR](https://github.com/mehmetpekmezci/gtu-rir) | GTU-RIR dataset, comprises more than 15,000 room impulse responses (RIRs). To collect this dataset, we developed a semi-automated sound recording system, and the entire process of constructing this system and extracting the RIRs is thoroughly explained in our GitHub repository(https://github.com/mehmetpekmezci/gtu-rir) | 2024 | [GTU-RIR - Gebze Technical Universiry Room Impulse Response Dataset for Acoustic Learning](https://gtu-my.sharepoint.com/:u:/g/personal/mpekmezci_gtu_edu_tr/Ec9dwMtiymlOuu_NSv5yT0YBeLwiFk8lwdhBpWrSCtPcZg?e=Xu50ok) | :heavy_check_mark: 14 | | [MIRACLE](https://depositonce.tu-berlin.de/items/b079fd1c-999f-42cb-afd2-bcd34de6180b) | The MIRACLE dataset contains a total of 856,128 single-channel impulse responses acquired across four different measurement scenarios with a planar 64-channel microphone array. A regular grid of 64 × 64 source locations was sampled for two different source plane to microphone array distances. The dataset also contains measurements on a densely sampled 33 × 33 grid for the short distance, as well as measurements with the presence of a reflective panel. | 2023 | [MIRACLE - Microphone Array Impulse Response Dataset for Acoustic Learning](https://doi.org/10.1186/s13636-024-00352-8) | :heavy_check_mark: 15 | | [SoundCam](https://sites.google.com/view/soundcam) |It includes 5,000 10-channel real-world measurements of room impulse responses and 2,000 10-channel recordings of music in three different rooms, including a controlled acoustic lab, an in-the-wild living room, and a conference room, with different humans in positions throughout each room. | 2023 | [SoundCam: A Dataset for Tasks in Tracking and Identifying Humans from Real Room Acoustics](https://nips.cc/virtual/2023/poster/73471) | :heavy_check_mark: 16 | | [Arni](https://zenodo.org/record/6985104#.YwffZuzMIeY) | 132,037 RIRs measured using 5342 configurations of 55 acoustic panels in the variable acoustics laboratory Arni at Acoustics Lab of Aalto University. | 2022 | [Calibrating the Sabine and Eyring formulas](https://asa.scitation.org/doi/full/10.1121/10.0013575) | 17 | | [Motus](https://doi.org/10.5281/zenodo.4923187) | 3,320 higher-order Ambisonic RIRs measured using an Eigenmike em32, 4 loudspeaker positions, and 830 furniture configurations inside a single room at Acoustics Lab of Aalto University. Spherical photographs and 3D models are available for each measurement.| 2021 | [A dataset of higher-order Ambisonic room impulse responses and 3D models measured in a room with varying furniture](https://doi.org/10.1109/I3DA48870.2021.9610933) | 18 | | [dEchorate](https://zenodo.org/record/5562386#.YflQNlvMLu0) | 1800 annotated RIRs obtained from 6 arrays of 5 microphones each, 6 sound sources and 11 different acoustic conditions. | 2021 | [dEchorate: a Calibrated Room Impulse Response Dataset for Echo-aware Signal Processing](https://arxiv.org/abs/2104.13168) | 19 | | [MeshRIR](https://sh01k.github.io/MeshRIR/) | 4410 mono RIRs recorded in very dense grids in a moderately reverberant room with accurate coordinates. | 2021 | [MeshRIR: A Dataset of Room Impulse Responses on Meshed Grid Points For Evaluating Sound Field Analysis and Synthesis Methods](https://arxiv.org/abs/2106.10801) | 20 | | [BUT Reverb Database](https://speech.fit.vutbr.cz/software/but-speech-fit-reverb-database) | 1300+ mono channel RIRs recorded in 8 rooms | 2019 | [Building and evaluation of a real room impulse response dataset](https://ieeexplore.ieee.org/document/8717722) | :heavy_check_mark: 21 | | [MIT IR Survey](https://mcdermottlab.mit.edu/Reverb/IR_Survey.html) | 271 mono channel RIRs all recorded in distinct places | 2016 | [Statistics of natural reverberation enable perceptual separation of sound and space](https://www.pnas.org/content/113/48/E7856) | :heavy_check_mark: 22 | | [ACE Challenge](http://www.ee.ic.ac.uk/naylor/ACEweb/index.html) | {1,2,3,5,8,32} channel RIRs recorded in 7 rooms | 2015 | [The ACE challenge — Corpus description and performance evaluation](https://ieeexplore.ieee.org/document/7336912) | 23 | | [Multichannel Impulse Response Database](https://www.eng.biu.ac.il/gannot/downloads/) | 234 8-channel RIRs recorded in the same room with 3 levels of reverberation and different microphone array spacings | 2014 | [Multichannel audio database in various acoustic environments](https://ieeexplore.ieee.org/document/6954309) | :heavy_check_mark: 24 | | [REVERB Challenge](https://reverb2014.dereverberation.com/) | 24 8-channel RIRs recorded in small, medium, and large rooms | 2013 | [The reverb challenge: A common evaluation framework for dereverberation and recognition of reverberant speech](https://ieeexplore.ieee.org/document/6701894) | :heavy_check_mark: 25 | | [OpenAIR](https://www.openairlib.net/) | Ambisonic B format RIRs recorded in over 46 (still increasing) environments | 2010 | [Openair: An interactive auralization web resource and database](https://www.aes.org/e-lib/browse.cfm?elib=15648) | :heavy_check_mark: 26 | | [C4DM RIR database](http://isophonics.net/content/room-impulse-response-data-set) | 468 mono or ambisonic B format RIRs recorded in 3 large environments | 2010 | [Database of Omnidirectional and B-Format Impulse Responses](https://ieeexplore.ieee.org/document/5496083) 27 | | [Aachen impulse response database](http://www.iks.rwth-aachen.de/en/research/tools-downloads/databases/aachen-impulse-response-database/) | 344 binaural RIRs measured with a dummy head in 5 environments including a church | 2009 | [A Binaural Room Impulse Response Database for the Evaluation of Dereverberation Algorithms](https://ieeexplore.ieee.org/abstract/document/5201259) | :heavy_check_mark: 28 | | [RWCP Sound Scene Database](http://research.nii.ac.jp/src/en/RWCP-SSD.html) | 143 multi-channel RIRs recorded in 14 rooms | 2000 | [Sound scene data collection in real acoustical environments](https://library.naist.jp/dspace/bitstream/handle/10061/7746/JourAcouSocJaE_20_3_225.pdf?sequence=1) | :heavy_check_mark: 29 | 30 | # Contribute 31 | Collecting real-world impulse responses is not easy. This repo tries to keep up with new real-world datasets available through volunteers. If you know publicly available datasets that are not listed here, you are welcome to create a pull request by adding a new entry to the list (and optionally the script to download & organize it). When writing the description, please highlight how many IRs and environments and what channel format are invovled in this dataset. 32 | 33 | # Reference 34 | Please properly cite whichever datasets you use in your paper. It would be great if you can also provide a link to this page (e.g., as a footnote, not a citation) so that others may find it useful. 35 | --------------------------------------------------------------------------------