The performance of speaker recognition systems drop significantly under noisy conditions. To improve robustness, we have recently proposed novel auditory features and a robust spe...
Missing data techniques have been recently applied to speaker recognition to increase performance in noisy environments. The drawback of these techniques is the vulnerability of t...
It is well known that MFCC based speaker identification (SID) systems easily break down under mismatched training and test conditions. One such mismatch occurs when a SID system ...
Noisy or distorted video/audio training sets represent constant challenges in automated identification and verification tasks. We propose the method of Mutual Interdependence An...
Speaker recognition remains a challenging task under noisy conditions. Inspired by auditory perception, computational auditory scene analysis (CASA) typically segregates speech by...