Target Speaker Extraction

Target speaker extraction (TSE) aims to isolate a specific speaker's voice from overlapping speech mixtures, a crucial task for applications like hearing aids and personalized interfaces. Current research emphasizes improving robustness and generalization, focusing on model architectures like transformers and convolutional neural networks, often incorporating curriculum learning and data augmentation techniques to enhance performance, particularly in noisy or reverberant environments. The development of efficient and accurate TSE methods holds significant promise for advancing speech processing technologies and improving human-computer interaction in challenging acoustic scenarios.