Blaster: An Off-Grid Method For Blind And Regularized Acoustic Echoes Retrieval

Acoustic echoes retrieval is a research topic that is gaining importance in many speech and audio signal processing applications (speech enhancement, source separation, dereverberation, room geometry estimation, etc.). This work proposes an novel approach to retrieve acoustic echoes timing off-grid and blindly, i.e., from a multichannel recording of an unknown sound source such as speech. It builds on the recent framework of continuous dictionaries. In contrast with existing methods, the proposed approach does not rely on parameter tuning nor peak picking techniques by working directly in the parameter space of interest. The accuracy and robustness of the method are assessed on challenging simulated setups with varying noise and reverberation levels and are compared to two state-of-the-art methods.