Sound Source Localization Based on GCC-PHAT With Diffuseness Mask in Noisy and Reverberant Environments

• Published in: IEEE access Vol. 8; pp. 7373 - 7382
• Main Authors: Lee, Ran, Kang, Min-Seok, Kim, Bo-Hyun, Park, Kang-Ho, Lee, Sung Q, Park, Hyung-Min
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 2020; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Acoustics; Coherence; Communications systems; Diffuseness mask; Estimation; GCC-PHAT; Indexes; Localization; Microphones; Noise measurement; Phase transitions; Reverberation; Robustness; Sound; sound source localization; Sound sources; Spatial coherence; Time lag
• ISSN: 2169-3536; 2169-3536
• DOI: 10.1109/ACCESS.2019.2963768

Although sound source localization is a desirable technique in many communication systems and intelligence applications, the distortion caused by diffuse noise or reverberation makes the time delay estimation (TDE) between signals acquired by a pair of microphones a complicated and challenging problem. In this paper, we describe a method that can efficiently achieve sound source localization in noisy and reverberant environments. This method is based on the generalized cross-correlation (GCC) function with phase transform (PHAT) weights (GCC-PHAT) to achieve robustness against reverberation. In addition, to estimate the time delay robust to diffuse components and to further improve the robustness of the GCC-PHAT against reverberation, time-frequency(t-f) components of observations directly emitted by a point source are chosen by "inversed" diffuseness. The diffuseness that can be estimated from the coherent-to-diffuse power ratio (CDR) based on spatial coherence between two microphones represents the contribution of diffuse components on a scale of zero to one with direct sounds from a source modeled to be fully coherent. In particular, the "inversed" diffuseness is binarized with a very rigorous threshold to select highly reliable components for accurate TDE even in noisy and reverberant environments. Experimental results for both simulated and real-recorded data consistently demonstrated the robustness of the presented method against diffuse noise and reverberation.