Human judgment is the final authority in forensic speaker recognition, but the use of modern speaker verification systems with accurate algorithms to perform the task under various circumstances has a huge potential to help the expert. The ultimate goal is to improve the accuracy of automatic systems when challenging data is provided and find a methodology for human-aided speaker recognition systems. This work presents an evaluation of speaker recognition carried out by human listeners and a gender dependent i-vector recognizer with a strategy for fusion of the decision process. Our experiments with HASR 2010 and HASR 2012 data indicate complementarity in the performance of the automatic system and the naive listeners decisions.
Bibliographic reference. Hautamäki, Rosa González / Hautamäki, Ville / Rajan, Padmanabhan / Kinnunen, Tomi (2013): "Merging human and automatic system decisions to improve speaker recognition performance", In INTERSPEECH-2013, 2519-2523.