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.
Highlights
The existing sound source localization methods can be divided into three categories [7,8,9,10,11]: Time delay estimation (TDE)-based two-step localization methods, methods based on highresolution spectral estimation, and beamforming methods based on the maximum steered response power
There were 1080 frames for each signal, in which 200 frames with a larger short-time energy were selected for sound source localization using steered response power (SRP)-PHAT
Among the existing sound source localization algorithms, SRP-PHAT has the advantages of anti-noise and robustness against reverberation
Summary
Sound source localization is a technology to determine the position of the objective sound source by analyzing sound signals and has been applied in many areas, such as speaker localization in teleconferencing, the noise testing of wind turbines, sound discrimination of robots, car whistle identification, etc. [1,2,3,4,5,6]. The TDE based two-step location methods first evaluate the time difference of the sound arrival at different elements of the microphone array and identify the sound source according to the geometry configuration of the microphone array These methods have simple principles and high efficiency; the TDE performance drops markedly under relatively heavy noise or reverberation. Cai et al [16], Wan et al [17,18], Zhao et al [19], Badía et al [20], and Nunes et al [21] did similar work These suggested methods do improve SRP-PHAT for specific situations, they ask for either strict conditions or complicated computation.
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