The Gaussian mixture model (GMM) is a currently used method for speaker recognition. The fuzzy GMM (FGMM) proposed in our previous work is a fuzzy clustering-based modification of the GMM. Although both the FGMM and the GMM are capable of achieving high identification accuracy, they have a common disadvantage in the problem of sensitivity to outliers. This paper presents an improvement for the FGMM to handle this problem. Experimental results on 16 speakers using the TI46 database are also reported.
|Number of pages||4|
|Publication status||Published - 1999|
|Event||Proceedings of the 1999 3rd International Conference on Knowledge-Based Intelligent Information Engineering Systems (KES '99) - Adelaide, Aust|
Duration: 31 Aug 1999 → 1 Sep 1999
|Conference||Proceedings of the 1999 3rd International Conference on Knowledge-Based Intelligent Information Engineering Systems (KES '99)|
|Period||31/08/99 → 1/09/99|