@article{8700074,
  abstract     = {{Localization of multiple speakers using microphone arrays remains a challenging problem, especially in the presence of noise and reverberation. State-of-the-art localization algorithms generally exploit the sparsity of speech in some representation for this purpose. Whereas the broadband approaches exploit time-domain sparsity for multi-speaker localization, narrowband approaches can additionally exploit sparsity and disjointness in the time-frequency representation. Broadband approaches are robust to spatial aliasing but do not optimally exploit the frequency domain sparsity, leading to poor localization performance for arrays with short inter-microphone distances. Narrowband approaches, on the other hand, are vulnerable to spatial aliasing, making them unsuitable for arrays with large inter-microphone spacing. Proposed here is an approach that decomposes a signal spectrum into a weighted sum of broadband spectral components (atoms) and then exploits signal sparsity in the time-atom representation for simultaneous multiple source localization. The decomposition into atoms is performed in situ using non-negative matrix factorization (NMF) of the short-term amplitude spectra and the localization estimate is obtained via a broadband steered-response power (SRP) approach for each active atom of a time frame. This SRP-NMF approach thereby combines the advantages of the narrowband and broadband approaches and performs well on the multi-speaker localization task for a broad range of inter-microphone spacings. On tests conducted on real-world data from public challenges such as SiSEC and LOCATA, and on data generated from recorded room impulse responses, the SRP-NMF approach outperforms the commonly used variants of narrowband and broadband localization approaches in terms of source detection capability and localization accuracy.}},
  articleno    = {{13}},
  author       = {{Thakallapalli, Sushmita and Gangashetty, Suryakanth V. and Madhu, Nilesh}},
  issn         = {{1687-4722}},
  journal      = {{EURASIP JOURNAL ON AUDIO SPEECH AND MUSIC PROCESSING}},
  keywords     = {{Acoustics and Ultrasonics,Electrical and Electronic Engineering,Sound source localization,Direction-of-arrival,Non-negative matrix factorization,Spatial aliasing,Speech sparsity}},
  language     = {{eng}},
  pages        = {{18}},
  title        = {{NMF-weighted SRP for multi-speaker direction of arrival estimation : robustness to spatial aliasing while exploiting sparsity in the atom-time domain}},
  url          = {{http://dx.doi.org/10.1186/s13636-021-00201-y}},
  volume       = {{2021}},
  year         = {{2021}},
}

Altmetric

View in Altmetric

Web of Science

Times cited: