ISCA Archive Interspeech 2013
ISCA Archive Interspeech 2013

Sequential model adaptation for speaker verification

Jun Wang, Dong Wang, Xiaojun Wu, Thomas Fang Zheng, Javier Tejedor

GMM-UBM-based speaker verification heavily relies on well-trained UBMs. In practice, it is not often easy to obtain a UBM that fully matches the acoustic channel in operation. In a previous study, we proposed to address this problem by a novel sequential UBM adaptation approach based on MAP. This work extends the study by applying the sequential approach to speaker model adaptation. In addition, we investigate a new feature-space sequential adaptation approach based on feature MAP linear regression (fMAPLR) and compare it with the previously proposed model-space MAP approach. We find that these two approaches are complementary and can be combined to deliver additional performance gains. The experiments conducted on a time-varying speech database demonstrate that the proposed MAP-fMAPLR approach leads to significant EER reduction with two mismatched UBMs (25% and 39% respectively).


doi: 10.21437/Interspeech.2013-410

Cite as: Wang, J., Wang, D., Wu, X., Zheng, T.F., Tejedor, J. (2013) Sequential model adaptation for speaker verification. Proc. Interspeech 2013, 2460-2464, doi: 10.21437/Interspeech.2013-410

@inproceedings{wang13d_interspeech,
  author={Jun Wang and Dong Wang and Xiaojun Wu and Thomas Fang Zheng and Javier Tejedor},
  title={{Sequential model adaptation for speaker verification}},
  year=2013,
  booktitle={Proc. Interspeech 2013},
  pages={2460--2464},
  doi={10.21437/Interspeech.2013-410}
}