Soundscape Augmentation

Soundscape augmentation aims to improve the perceived quality of acoustic environments by adding beneficial sounds ("maskers") to reduce the negative impact of unwanted noise. Current research heavily utilizes artificial intelligence, particularly deep learning models (including convolutional neural networks and attention-based architectures), to automatically select and adjust these maskers based on real-time acoustic analysis and even multimodal inputs like visual data and user demographics. This field is significant for advancing noise pollution mitigation strategies, offering data-driven, personalized approaches to enhance urban soundscapes and improve human well-being.