Audio Effect

Audio effect research focuses on developing and understanding methods for manipulating audio signals, aiming to improve audio quality, create new sounds, and automate audio production processes. Current research emphasizes the use of neural networks, particularly recurrent and convolutional architectures, often integrated with differentiable digital signal processing (DDSP) techniques, to model, control, and even remove audio effects. This work is significant for advancing both the artistic creation of audio and the efficiency of audio production workflows, with applications ranging from e-commerce video enhancement to sophisticated music production tools. Furthermore, research is exploring novel methods for representing and manipulating audio effects using embeddings and other representation learning techniques.