Abstract: A metaverse application generates a first abuse score for the audio stream associated with a first user based on rules that analyze user signals, wherein the user signals include one or more selected from the group of one or more second users muting the first user, a history of past moderation actions associated with the first user, one or more third users blocking the first user, and combinations thereof. The metaverse application includes an audio-classifier model that obtains a second abuse score for an audio stream associated with the first user, wherein the audio stream is provided as input to the audio-classifier model. The metaverse application determines that the first user is committing abuse based on one or more selected from the group of the first abuse score, the second abuse score, and combinations thereof exceeding a threshold score value. Responsive to determining that the first user is committing abuse, the metaverse application performs a remedial action.

Abstract: A metaverse application generates a first abuse score for the audio stream associated with a first user based on rules that analyze user signals, wherein the user signals include one or more selected from the group of one or more second users muting the first user, a history of past moderation actions associated with the first user, one or more third users blocking the first user, and combinations thereof. The metaverse application includes an audio-classifier model that obtains a second abuse score for an audio stream associated with the first user, wherein the audio stream is provided as input to the audio-classifier model. The metaverse application determines that the first user is committing abuse based on one or more selected from the group of the first abuse score, the second abuse score, and combinations thereof exceeding a threshold score value. Responsive to determining that the first user is committing abuse, the metaverse application performs a remedial action.