6. A system for speaker diarization, comprising: a processor; a storage medium storing pre-trained acoustic models of individual speakers and/or groups of speakers; a receiver for receiving speech data from multiple speakers; and a computer processor configured to divide the speech data into frames, determine for each of a plurality of frames a modified acoustic feature vector including elements representing for one or more of the pre-trained acoustic models, a probability that the speaker of the frame is the speaker of the pre-trained acoustic model, and segment or cluster the speech data using the modified feature vectors of the plurality of frames.
6. A system for speaker diarization, comprising: a processor; a storage medium storing pre-trained acoustic models of individual speakers and/or groups of speakers; a receiver for receiving speech data from multiple speakers; and a computer processor configured to divide the speech data into frames, determine for each of a plurality of frames a modified acoustic feature vector including elements representing for one or more of the pre-trained acoustic models, a probability that the speaker of the frame is the speaker of the pre-trained acoustic model, and segment or cluster the speech data using the modified feature vectors of the plurality of frames. 12. The system as claimed in claim 6 , including a speaker identification component for applying speaker identification to clustered segments using the pre-trained models.