P-Value Segment Selection Technique for Speaker Verification

This paper presents a segment selection technique for discarding portions of speech that result in poor discrimination ability in speaker verification tasks. Theory supporting the significance of a frame selection procedure for test segments, prior to making decisions, is also developed. This approach has the ability to reduce the effect of the acoustic regions of speech that are not accurately represented due to a lack of training data. Compared with a baseline system using both CMS and variance normalization, the proposed segment selection technique brings 24% relative reduction in error rate over the entire testing data of the 2002 NIST Dataset in terms of minimum DCF. For short test segments, i.e. less than 15 seconds, the novel frame dropping technique produces a significant relative error rate reduction of 23% in terms of minimum DCF.