Abstract
The present paper reports on an evaluation of Batvox 3.1 as part of the Speech Communication virtual special issue: Multi-laboratory evaluation of forensic voice comparison systems under conditions reflecting those of a real forensic case (forensic_eval_01). We were interested in the effect of the amount of training data on the performance of the system. We therefore tested Batvox 3.1 using different sized sets of data randomly selected from the forensic_eval_01 training data: one known-speaker-condition recording and one questioned-speaker-condition recording from each of 25, 50, 75, and 100 speakers. The results show that the performance of the system continued to improve as the amount of training data increased. Previously reported results for Batvox 4.1 (an i-vector PLDA system) were better than those for Batvox 3.1 (a GMM-UBM system).
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