Hu, YonggangSamarasinghe, Prasanga N.Abhayapala, Thushara D.2025-12-172025-12-1797817281112301931-1168ORCID:/0000-0002-5589-4203/work/161744178https://hdl.handle.net/1885/733796070This paper proposes a data-driven source localization approach under a noisy and reverberant environment, using a newly defined feature named relative harmonic coefficients (RHC) in the modal domain. Being independent of the source signal, the RHC is capable of localizing a sound source(s) located at unknown position(s). Two distinctive multi-view Gaussian process (MVGP), (i) multi-frequency views and (ii) multi-mode views, are developed for Gaussian process regression (GPR) to reveal the mapping function from the RHC to the corresponding source location. We evaluate the effectiveness of the algorithm for single source localization while the underlying concepts proposed can be extended to acoustic scenarios where multiple sources are active. Experimental results, using a spherical microphone array, confirm that the proposed algorithm has a faster speed and achieves competitive performance in comparison to the state-of-art algorithm.∗Thanks to Australian Research Council Linkage Grant Projects funding scheme (project no. LP160100379). Yonggang Hu is sponsored by CSC agency for funding. Thanks to Australian Research Council Linkage Grant Projects funding scheme (project no. LP160100379). Yonggang Hu is sponsored by CSC agency for funding.5enPublisher Copyright: © 2019 IEEE.Gaussian process regressionmulti-view Gaussian processRelative harmonic coefficientsSource localization201910.1109/WASPAA.2019.893722185078001864