Sound Source Localization for Robots (SSLR)
Description
The Sound Source Localization for Robots (SSLR) Dataset is a collection of real robot audio recordings for the development and evaluation of sound source localization methods. Its features are:
- We recorded the audio with the Softbank's robot Pepper.
- The data include robot ego noise and overlapping speech sources.
- The dataset is separated into three sections: loudspeaker recordings, human talker recordings and noise recordings.
- It can serve as a standard benchmark dataset for the research of learning-based sound localization techniques.
Reference
If you use the data for your research or publication, please cite the following paper (bib file, fulltext):
He, Weipeng, Petr Motlicek, and Jean-Marc Odobez. “Deep Neural Networks for Multiple Speaker Detection and Localization.” In 2018 IEEE International Conference on Robotics and Automation (ICRA), 2018.
Files
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The record is publicly accessible, but files are restricted to users with access.
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