Title : 
Two-way cluster voting to improve speaker diarisation performance
         
        
        
            Author_Institution : 
Dept. of Eng., Cambridge Univ., UK
         
        
        
        
        
            Abstract : 
Speaker diarisation is the task of automatically segmenting audio data and providing speaker labels for the resulting regions of audio. A cluster-voting scheme is described which takes the output from two speaker diarisation systems and produces a new output which aims to have a lower speaker diarisation error rate (DER) than either input. The scheme works in two stages: the first produces a set of possible outputs which minimise a distance metric based on the DER; the second votes between these alternatives to give the final output. Decisions where the inputs agree are always passed to the output and those where the inputs differ are re-evaluated in the final voting stage. Results are presented on the 6-show RT-03 broadcast news evaluation data; they show that the DER can be reduced by 1.64% and 2.56% absolute using this method when combining the best two Cambridge University and the best two MIT Lincoln Laboratory diarisation systems respectively.
         
        
            Keywords : 
decision making; error statistics; minimisation; speaker recognition; audio data segmentation; distance metric minimisation; error rate; speaker diarisation; speaker labels; two-way cluster voting; Broadcasting; Databases; Density estimation robust algorithm; Error analysis; Indexing; Laboratories; Performance analysis; Speech recognition; US Government; Voting;
         
        
        
        
            Conference_Titel : 
Acoustics, Speech, and Signal Processing, 2005. Proceedings. (ICASSP '05). IEEE International Conference on
         
        
            Conference_Location : 
Philadelphia, PA
         
        
        
            Print_ISBN : 
0-7803-8874-7
         
        
        
            DOI : 
10.1109/ICASSP.2005.1415223