A hybrid parametric-deep learning approach for sound event localization and detection
This is an incremental improvement for audio processing tasks like sound event localization and detection.
The paper tackles sound event localization and detection by combining parametric spatial audio analysis with deep learning, achieving a 2.6-fold reduction in localization error compared to the baseline.
This work describes and discusses an algorithm submitted to the Sound Event Localization and Detection Task of DCASE2019 Challenge. The proposed methodology relies on parametric spatial audio analysis for source localization and detection, combined with a deep learning-based monophonic event classifier. The evaluation of the proposed algorithm yields overall results comparable to the baseline system. The main highlight is a reduction of the localization error on the evaluation dataset by a factor of 2.6, compared with the baseline performance.