Speech Enhancement Module

Speech enhancement modules aim to improve the quality and intelligibility of speech signals by reducing noise and interference, thereby enhancing downstream tasks like speech recognition and translation. Current research focuses on developing universal enhancement frameworks adaptable to various applications, employing dynamic neural networks and multi-task learning approaches to jointly optimize speech enhancement with other processing steps. This work is crucial for advancing real-time applications such as simultaneous speech translation and improving the robustness of speech processing systems in challenging acoustic environments, impacting fields ranging from human-computer interaction to assistive technologies.