To extend the proposed approach to discover sounding actions in multi-person egocentric videos, we can modify the model to handle multiple individuals in the scene. This can be achieved by incorporating additional modalities such as depth information or skeleton data to track the movements and interactions of each person. By including these modalities, the model can learn to associate specific sounds with the actions of individual persons in the video. Additionally, the model can be trained to differentiate between sounds produced by different individuals in the scene, enabling the discovery of sounding actions in a multi-person context.