Acoustic Signal

Acoustic signal analysis focuses on extracting meaningful information from sound waves for various applications, primarily using machine learning to classify and interpret complex acoustic patterns. Current research heavily utilizes deep learning architectures, such as convolutional neural networks (CNNs), recurrent neural networks (RNNs), and transformers, often coupled with techniques like Mel-frequency cepstral coefficients (MFCCs) for feature extraction. This field is significantly impacting diverse sectors, enabling advancements in areas ranging from industrial fault detection and predictive maintenance to environmental monitoring and agricultural practices through improved automation and efficiency.