SALSA: Spatial Cue-Augmented Log-Spectrogram Features for Polyphonic Sound Event Localization and Detection

@article{Nguyen2022SALSASC,
  title={SALSA: Spatial Cue-Augmented Log-Spectrogram Features for Polyphonic Sound Event Localization and Detection},
  author={Thi Ngoc Tho Nguyen and Karn Nichakarn Watcharasupat and Ngoc Khanh Nguyen and Douglas L. Jones and Woonseng Gan},
  journal={IEEE/ACM Transactions on Audio, Speech, and Language Processing},
  year={2022},
  volume={30},
  pages={1749-1762}
}
Sound event localization and detection (SELD) consists of two subtasks, which are sound event detection and direction-of-arrival estimation. While sound event detection mainly relies on time-frequency patterns to distinguish different sound classes, direction-of-arrival estimation uses amplitude and/or phase differences between microphones to estimate source directions. As a result, it is often difficult to jointly optimize these two subtasks. We propose a novel feature called <italic>Spatial… 

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  • 2022
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