Cocktail Party

The "cocktail party effect," the ability to focus on a single conversation amidst background noise, is a central challenge in speech separation and target speaker extraction. Current research focuses on leveraging large language models (LLMs) to guide speech separation, using textual cues to identify target speakers and improve robustness, and developing new datasets with ground truth labels to better evaluate these models. This work is significant for advancing human-computer interaction, improving assistive technologies like hearing aids, and enhancing privacy-preserving techniques in federated learning where protecting individual data during model training is crucial.