A real-time text-independent speaker identification system

The paper presents a real-time speaker identification system based on the analysis of the audio track of a video stream. The system has been employed in the context of automatic video segmentation. It uses features evaluated in both the time and frequency domains. Their combined use significantly improve the performance of the system. Experiments have been carried on a database extracted from over one hour of television news, including 10 speakers. The obtained results confirm the effectiveness of the approach, showing an error rate less then 1% when the time interval used for identifying a speaker is about 1.5 seconds.