Noise Masking

Noise masking, the process of selectively attenuating or altering audio signals, is a rapidly evolving field with applications ranging from speech enhancement and privacy protection to improving the performance of machine learning models. Current research focuses on developing sophisticated masking techniques, often employing deep learning architectures like transformers and variational autoencoders, to achieve targeted noise reduction or information concealment. These advancements have significant implications for improving the robustness and privacy of speech recognition systems, enhancing audio quality in various communication scenarios, and even informing the design of more effective human-computer interfaces and spacesuit technology.