The use of broad phonetic class models in speaker recognition

In this paper we investigate the use of broad phonetic class (BPC) models in a text independent speaker recognition task. These models can be used to bring down the variability due to the intrinsic differences between mutual phonetic classes in the speech material used for training of the speaker models. Combining BPC recognition with text independent speaker recognition moves a bit in the direction of text dependent speaker recognition: a task which is known to reach better performance. The performance of BPC modelling is compared to our baseline system using ergodic 5-state HMMs. The question which BPC contains most speaker specific information is addressed. Also, it is investigated if and how the BPC alignment is correlated with the state alignment from the baseline system to check the assumption that states of an ergodic HMM can model broad phonetic classes [3].