The SBM Matlab toolbox for “Supervised Binaural Mapping”, contains a set of functions and scripts for supervised binaural sound source separation and localization. The approach consists in learning the acoustic space of a system using a set of white-noise measurements. Once the acoustic space is learned, it can be used…
The GLLiM toolbox v1.0 provides a set of Matlab functions allowing to learn a relationship between two spaces. It implements the hGLLiM algorithm described in detail in: A. Deleforge, F. Forbes, and R. Horaud. High-Dimensional Regression with Gaussian Mixtures and Partially-Latent Response Variables. Statistics and Computing. 2014. The article is available…
The AVASM dataset is a set of audio-visual recordings made the dummy head POPEYE in real world conditions. It consists of binaural recordings of a single static sound source emitting white noise or speech from different positions. The sound source is a loud-speaker equipped with a visual target manually placed at different…
The CAMIL dataset is a unique set of audio recordings made with the robot POPEYE. The dataset was gathered in order to investigate audio-motor contingencies from a computational point of view and experiment new auditory models and techniques for Computational Auditory Scene Analysis. The version 0.1 of the dataset was…
