Noise Suppression

Noise suppression aims to improve audio quality by removing unwanted sounds, focusing on enhancing speech intelligibility and overall listening experience. Current research emphasizes developing efficient and adaptable deep learning models, such as recurrent neural networks (RNNs) and transformers, often incorporating multi-modal approaches (e.g., using ultrasound) or personalized techniques to better handle diverse noise types and speaker characteristics. These advancements are crucial for improving various applications, including teleconferencing, hearing aids, and voice-controlled devices, by enabling clearer and more robust audio processing in real-world conditions.