A new domain compensation framework is proposed for speaker verification.
This framework can be applied in both unsupervised and supervised manner.
Deep neural networks are used to generate domain dependent discriminative features.
Domain mismatches are compensated in the vector-based speaker-modeling step.
Performances on NIST SRE2010 task are competitive to the state-of-the-art techniques.