1. A method for speaker diarization, comprising the steps of: obtaining pre-trained acoustic models of individual speakers and/or groups of speakers; receiving speech data with multiple speakers; dividing the speech data into frames; and for a frame, determining an acoustic feature vector extended to include log-likelihood ratios of the pre-trained models in relation to a background population model; wherein said steps are implemented in either of: a) computer hardware configured to perform said steps, or b) computer software embodied in a non-transitory, tangible, computer-readable storage medium.