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A novel rank-based classifier combination scheme for speaker identification

Altincay, H
Demirekler, Mübeccel
In this paper, we propose a novel rank-based classifier combination scheme under uncertainty for speaker identification (SI). The combination is based on a heuristic method that uses Dempster-Shafer theory of evidence under some conditions. The method is based on the extraction of first and R-th level ranking statistics. Using these statistics, the pat tern classes are clustered into model sets where the classes in these sets share set specific properties. Some of these model sets are used to reflect the strengths and weaknesses where some others carr class dependent ranking statistics of the corresponding classifier. The experiments conducted on the Polycost database have shown that the proposed approach is more effective compared to some other rank-based combination schemes.