A new set of features for text-independent speaker identification

The success of a speaker identification system depends largely on the set of features used to characterize speaker-specific information. In this paper, we discuss a small set of low-level acoustic parameters that capture information about the speaker’s source, vocal tract size and vocal tract shape. We demonstrate that the set of eight acoustic parameters has comparable performance to the standard sets of 26 or 39 MFCCs for the speaker identification task. Gaussian Mixture Models were used for constructing speaker models. Index Terms: speaker identification, acoustic parameters,