The dEchorate dataset is a new database of measured multichannel Room Impulse Responses (RIRs) including annotations of early echo timings and 3D positions of microphones, real sources and image sourcesunder different wall configurations in a cuboid room.
These data provide a tool for benchmarking recentmethods inecho-awarespeech enhancement, room geometry estimation, RIR estimation, acoustic echoretrieval, microphone calibration, echo labeling and reflectors estimation.
The database is accompanied withsoftware utilities to easily access, manipulate and visualize the data as well as baseline methods forecho-related tasks.

Keywords: Echo-aware signal processing; Acoustic echoes; Room impulse response; Audio database; AcousticEcho Retrieval; Spatial Filtering; Room Geometry Estimation; Microphone arrays.

You can find a detailed explanation of the dEchorate dataset at: dEchorate: a Calibrated Room Impulse Response Database for Echo-aware Signal Processing

dEchorate has three main elements:

• the data on Zenodo
  • dataset in HDF5 format with python script;
  • dataset in SOFA format;
• the code for working with dEchorate (available in this repo);
• the code for reproducing the paper (available in this repo).

• 25 May 2022: v2.0.0 new dEchorate dataset
• 03 May 2020: v0.0.1 dEchorate project is alive

If you are using dEchorate and you want to cite us, please use

@article{dicarlo2021dechorate,
  title={dEchorate: a calibrated room impulse response dataset for echo-aware signal processing},
  author={{Di Carlo}, Diego and Tandeitnik, Pinchas and Foy, Cedri{\'c} and Bertin, Nancy and Deleforge, Antoine and Gannot, Sharon},
  journal={EURASIP Journal on Audio, Speech, and Music Processing},
  volume={2021},
  number={1},
  pages={1--15},
  year={2021},
  publisher={Springer}
}