2019/11/26 by Thi Ngoc Tho Nguyen, T. N. T. Nguyen, D. L. Jones +12
Computer Science · Engineering · #Audio and Speech Processing (eess.AS) #FOS: Computer and information sciences #FOS: Electrical engineering #Music Technology and Sound Studies #Music and Audio Processing #Sound (cs.SD) #Speech and Audio Processing #cs.SD #eess.AS #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.1911.11373
5 pages
arxiv created 2019/11/26 · openalex publication_date 2019/11/26 · arxiv updated 2019/11/27 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Sound event detection and sound event localization requires different features from audio input signals. While sound event detection mainly relies on time-frequency patterns to distinguish different event classes, sound event localization uses magnitude or phase differences between microphones to estimate source directions. Therefore, we propose a two-step system to do sound event localization and detection. In the first step, we detect the sound events and estimate the directions-of-arrival separately. In the second step, we combine the results of the event detector and direction-of-arrival estimator together. The obtained results show a significant improvement over the baseline solution for sound event localization and detection in DCASE 2019 task 3 challenge. Using the evaluation dataset, the proposed system achieved an F1 score of 93.4% for sound event detection and an error of 5.4 degrees for direction-of-arrival estimation, while the winning solution achieved an F1 score of 94.7% and an angle error of 3.7 degrees respectively.