ISCA Archive Interspeech 2005
ISCA Archive Interspeech 2005

Mixture of support vector machines for text-independent speaker recognition

Zhenchun Lei, Yingchun Yang, Zhaohui Wu

In this paper, the mixture of support vector machines is proposed and applied to text-independent speaker recognition. The mixture of experts is used and is implemented by the divide-and-conquer approach. The purpose of adopting this idea is to deal with the large scale speech data and improve the performance of speaker recognition. The principle is to train several parallel SVMs on the subsets of the whole dataset and then combine them in the distance or probabilistic fashion. The experiments have been run on the YOHO database, and the results show that the mixture model is superior to the basic Gaussian mixture model.


doi: 10.21437/Interspeech.2005-638

Cite as: Lei, Z., Yang, Y., Wu, Z. (2005) Mixture of support vector machines for text-independent speaker recognition. Proc. Interspeech 2005, 2041-2044, doi: 10.21437/Interspeech.2005-638

@inproceedings{lei05b_interspeech,
  author={Zhenchun Lei and Yingchun Yang and Zhaohui Wu},
  title={{Mixture of support vector machines for text-independent speaker recognition}},
  year=2005,
  booktitle={Proc. Interspeech 2005},
  pages={2041--2044},
  doi={10.21437/Interspeech.2005-638}
}