Speaker detection using multi-speaker audio files for both enrollment and test

This paper focuses on speaker detection using multispeaker files both for the enrollment phase and for the test phase. This task was introduced during the 2002 NIST speaker recognition evaluation campaign. Enrollment data is composed of three two-speaker files. Test files are also two-speaker records. The system presented here uses a speaker segmentation process based on an HMM conversation model followed by a speaker matching technique to produce one-speaker segments. Speaker detection is then achieved using AMIRAL, LIA´s GMM-based speaker verification system. Validation of the proposed strategy is done using extracts from the NIST 2002 results.