Acoustic Scene Classification

Acoustic scene classification (ASC) aims to automatically identify the environment of an audio recording based on its acoustic characteristics. Current research heavily focuses on improving data efficiency and model efficiency, often employing convolutional neural networks (CNNs), spectrogram transformers (ASTs), and knowledge distillation techniques to achieve high accuracy with limited training data and computational resources. ASC advancements have significant implications for various applications, including environmental monitoring, assistive technologies, and content verification, by enabling robust and efficient audio analysis in diverse real-world settings.