Overview and Evaluation of Sound Event Localization and Detection in DCASE 2019

Abstract

Sound event localization and detection is a novel area of research that emerged from the combined interest of analyzing the acoustic scene in terms of the spatial and temporal activity of sounds of interest. This paper presents an overview of the first international evaluation on sound event localization and detection, organized as a task of the DCASE 2019 Challenge. A large-scale realistic dataset of spatialized sound events was generated for the challenge, to be used for training of learning-based approaches, and for evaluation of the submissions in an unlabeled subset. The overview presents in detail how the systems were evaluated and ranked and the characteristics of the best-performing systems. Common strategies in terms of input features, model architectures, training approaches, exploitation of prior knowledge, and data augmentation are discussed. Since ranking in the challenge was based on individually evaluating localization and event classification performance, part of the overview focuses on presenting metrics for the joint measurement of the two, together with a reevaluation of submissions using these new metrics. The new analysis reveals submissions that performed better on the joint task of detecting the correct type of event close to its original location than some of the submissions that were ranked higher in the challenge. Consequently, ranking of submissions which performed strongly when evaluated separately on detection or localization, but not jointly on both, was affected negatively.

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• L3DAS22 Challenge: Learning 3D Audio Sources in a Real Office Environment
• SALSA-Lite: A Fast and Effective Feature for Polyphonic Sound Event Localization and Detection with Microphone Arrays
• AI-based soundscape analysis: Jointly identifying sound sources and predicting annoyance
• Few-shot Class-incremental Audio Classification Using Dynamically Expanded Classifier with Self-attention Modified Prototypes
• A Dataset of Dynamic Reverberant Sound Scenes with Directional Interferers for Sound Event Localization and Detection
• Self-supervised Learning of Audio Representations from Audio-Visual Data using Spatial Alignment
• ACCDOA: Activity-Coupled Cartesian Direction of Arrival Representation for Sound Event Localization and Detection
• A Review on Sound Source Localization in Robotics: Focusing on Deep Learning Methods
• An Improved Event-Independent Network for Polyphonic Sound Event Localization and Detection
• Spatial mixup: Directional loudness modification as data augmentation for sound event localization and detection
• L3DAS21 Challenge: Machine Learning for 3D Audio Signal Processing
• USM-SED - A Dataset for Polyphonic Sound Event Detection in Urban Sound Monitoring Scenarios
• What Makes Sound Event Localization and Detection Difficult? Insights from Error Analysis
• TASK3 DCASE2021 Challenge: Sound event localization and detection using squeeze-excitation residual CNNs