Fast Sound Source Localization Based on SRP-PHAT Using Density Peaks Clustering

Abstract

Sound source localization has been increasingly used recently. Among the existing techniques of sound source localization, the steered response power–phase transform (SRP-PHAT) exhibits considerable advantages regarding anti-noise and anti-reverberation. When applied in real-time situations, however, the heavy computational load makes it impossible to localize the sound source in a reasonable time since SRP-PHAT employs a grid search scheme. To solve the problem, an improved procedure called ODB-SRP-PHAT, i.e., steered response power and phase transformation with an offline database (ODB), was proposed by the authors. The basic idea of ODB-SRP-PHAT is to determine the possible sound source positions using SRP-PHAT and density peak clustering before real-time localization and store the identified positions in an ODB. Then, at the online positioning stage, only the power values of the positions in the ODB will be calculated. When used in real-time monitoring, e.g., locating the speaker in a video conference, the computational load of ODB-SRP-PHAT is significantly smaller than that of SRP-PHAT. Simulations and experiments under a real environment verified the high localization accuracy with a small computational load of ODB-SRP-PHAT. In addition, the advantages of anti-noise and anti-reverberation remained. The suggested procedure displayed good applicability in a real environment.