Detection of Speaker Change Points in Conversational Speech

An important preprocessing step in many automatic speech segmentation and speaker clustering systems is the accurate detection of speaker change points, the times when one speaker stops talking and another begins. However, this becomes very difficult in conversational speech since utterance lengths can be extremely short, speaker changes occur frequently, speakers may talk over one another (co-channel interference), and the recording environment and/or communication channel is sub-optimal or degraded. Modern aviation systems can benefit from this research as a pre-processing stage in a variety of applications. Examples include automatic segmentation and clustering of pilot/air traffic controller communications, detection of a third or unauthorized speaker in commercial airline cockpits, and automatic transcription of cockpit audio recordings. This research presents an approach to detecting speaker change points using information obtained from voiced speech segments. This permits taking advantage of the facts that (1) speaker starting and stopping information should be contained between segments of voiced speech and (2) voiced speech contains the most useful speaker identifiable information. The technique presented here shows promise as an enhancement to currently available change point detection algorithms.