In this paper, we propose to apply Hadamard Error-Correcting Output Code (Hadamard ECOC) to extend binary classifier for multi-class classification problems. Hadamard ECOC is easy to construct and is suitable for any number of classes. We combine it with binary support vector machine (SVM) to solve the multi-class problem of speaker identification, which takes advantage of error correcting ability of Hadamard ECOC and powerful classification ability of SVM. Compared to the traditional "1-against-rest" method, the experiment result shows that Hadamard ECOC approach has much better and more stable performance for the multi-class problem and is robust on different rules mapping rules between ECOCs and classes.
Cite as: Yin, A.-r., Xie, X., Kuang, J. (2005) Using Hadamard ECOC in multi-class problems based on SVM. Proc. Interspeech 2005, 3125-3128, doi: 10.21437/Interspeech.2005-672
@inproceedings{yin05_interspeech,
author={An-rong Yin and Xiang Xie and Jingming Kuang},
title={{Using Hadamard ECOC in multi-class problems based on SVM}},
year=2005,
booktitle={Proc. Interspeech 2005},
pages={3125--3128},
doi={10.21437/Interspeech.2005-672}
}