Warping path and gross spectrum information for speaker verification under degraded condition

This work explores the nature of warping path and the shape of the gross spectrum for speaker information in text-dependent speaker verification under degraded condition. The nature of warping path is observed to follow a similar trend for given speaker across different sessions, due to the style of spoken delivery. The deviation of the warping path from the diagonal is taken as feature for discrimination amongst different speakers. Also the shape of the gross spectrum in low frequency band is similar for a given speaker across sessions. The correlation is found between train and test utterances gross spectra for verification. The warping path distortion (WPD) and gross spectrum correlation (GSC) features are derived for speaker verification. These features are evaluated for speech data collected over a speaker verification system in a practical setting. The proposed features are found to have robust speaker information, which improve the performance in combination with mel frequency cepstral coefficient (MFCC) features.