Acoustic Localization using Spatial Probability in Noisy and Reverberant Environments - Braun, Sebastian; Tashev, Ivan (Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA), 2019)
In realistic acoustic sound source localization scenarios, we oftenencounter not only the presence of multiple simultaneous sound sources, but also reverberation and noise. We propose a novel multi-source localization method based on the spatial sound presence probability (SSPP). The SSPP can be computed using prior knowl-edge of the anechoic relative transfer functions (RTFs), which incorporate magnitude and phase information, and makes the approach general for any device and geometry. From the SSPP we can not only obtain multiple simultaneous sound source direction estimates,but also their spatial presence probability. The SSPP can be used for a probabilistic update of the estimated directions, and can further be used to determine the dominant sound source. We demonstrate the robustness of our method in challenging non-stationary scenarios for single- and multi-speaker localization in noisy and reverberant conditions. The proposed method still localizes a sound source at 8 m with an average error below 7 degrees.