Sound Source Localization for Robots (SSLR)

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.