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Found 3 papers, 2 papers with code
Selective-Memory Meta-Learning with Environment Representations for Sound Event Localization and Detection
In addition, we introduce environment representations to characterize different acoustic settings, enhancing the adaptability of our attenuation approach to various environments.
META-SELD: Meta-Learning for Fast Adaptation to the new environment in Sound Event Localization and Detection
For learning-based sound event localization and detection (SELD) methods, different acoustic environments in the training and test sets may result in large performance differences in the validation and evaluation stages.
Sound Event Localization and Detection for Real Spatial Sound Scenes: Event-Independent Network and Data Augmentation Chains
Our system submitted to the DCASE 2022 Task 3 is based on our previous proposed Event-Independent Network V2 (EINV2) with a novel data augmentation method.
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