The I3A submission for the recent NIST 2012 speaker recognition evaluation (SRE) was based on the i-vector approach with a multichannel PLDA classifier. This PLDA is modified so that, for each i-vector, the between-class covariance depends on the type of channel where the segment was recorded (telephone, interviews, clean, noisy, etc). In this paper, we present the description of our submission and a detailed post-evaluation analysis of the results. We analyze several factors affecting performance: enrollment data selection, classifier type, scoring technique, calibration, known and unknown non-targets, target speakers included or not in development, segment duration, noise level and noise type. Some of these factor are new in this evaluation. After post-evaluation, actual costs improve by 15.43% depending on the common condition.
Bibliographic reference. Villalba, Jesús / Lleida, Eduardo / Ortega, Alfonso / Miguel, Antonio (2013): "The I3a speaker recognition system for NIST SRE12: post-evaluation analysis", In INTERSPEECH-2013, 3679-3683.