Experiments on using vocal tract estimates of nasal stops for speaker verification

Nasal stops have been recognized as an important source of speaker-discriminating features. The nasal cavity is, with the exception of the velar junction, independent of articulatory movements. As the complex nasal structure varies from person to person, features dependent upon nasal acoustics may have low within-speaker and high between-speaker variability. In this study we use a Bayesian estimation technique to obtain reflection coefficients of a branched-tube model of the combined nasal and oral tract. These are then used as parameters in speaker verification experiments. The performance is evaluated on the basis of speakers from the TIMIT corpus as well as the Kiel corpus and is compared with that of a system based on Mel frequency cepstral coefficient (MFCC) features. Fusion of both systems indicates that the two approaches offer complementary information.