A computer-implemented method for snore attribution, comprising: capturing audio using a microphone ; detecting a plurality of snores in the captured audio; determining that a first set of snores of said plurality of snores belongs to a first individual and that a second set of snores of said plurality of snores belongs to a second individual using a trained model ; playing for a user a subset of the snores of said first set and a subset of the snores of said second set ; for each played snore, prompting the user via a user interface to provide input whether or not the played snore belongs to the user; receiving said input from the user via the user interface; and attributing the first set of snores or the second set of snores to the user based on said input, wherein a multidimensional vector space embedding of each detected snore is formed, and wherein determining that a first set of snores of said plurality of snores belongs to a first individual and that a second set of snores of said plurality of snores belongs to a second individual using a trained model includes: - the trained model causing the embeddings of the snores of the first individual to be located in a first subspace in a vector space and the embeddings of the snores of the second individual to be located in a second, different subspace in said vector space ; - clustering the embeddings located in the first subspace to form said first set of snores ; and - clustering the embeddings located in the second subspace to form said second set of snores , wherein the method does not know anything snoring-related about the user beforehand. capturing audio using a microphone ; detecting a plurality of snores in the captured audio; determining that a first set of snores of said plurality of snores belongs to a first individual and that a second set of snores of said plurality of snores belongs to a second individual using a trained model ; playing for a user a subset of the snores of said first set and a subset of the snores of said second set ; for each played snore, prompting the user via a user interface to provide input whether or not the played snore belongs to the user; receiving said input from the user via the user interface; and attributing the first set of snores or the second set of snores to the user based on said input, wherein a multidimensional vector space embedding of each detected snore is formed, and wherein determining that a first set of snores of said plurality of snores belongs to a first individual and that a second set of snores of said plurality of snores belongs to a second individual using a trained model includes: - the trained model causing the embeddings of the snores of the first individual to be located in a first subspace in a vector space and the embeddings of the snores of the second individual to be located in a second, different subspace in said vector space ; - clustering the embeddings located in the first subspace to form said first set of snores ; and - clustering the embeddings located in the second subspace to form said second set of snores , - the trained model causing the embeddings of the snores of the first individual to be located in a first subspace in a vector space and the embeddings of the snores of the second individual to be located in a second, different subspace in said vector space ; - clustering the embeddings located in the first subspace to form said first set of snores ; and - clustering the embeddings located in the second subspace to form said second set of snores , wherein the method does not know anything snoring-related about the user beforehand. <EOS>