Speaker Extraction

Speaker extraction aims to isolate a target speaker's voice from a mixture of sounds, a crucial task with applications in enhancing speech intelligibility and enabling more robust speech processing systems. Current research focuses on developing sophisticated deep learning models, often employing attention mechanisms and incorporating multi-scale or multi-modal information (audio-visual, spatial cues) to improve accuracy and robustness in challenging acoustic environments. These advancements are driving progress in areas like personalized acoustic echo cancellation and improving the performance of downstream tasks such as speech recognition and diarization.