Several studies have been dedicated to the analysis and modeling of AM–FM modulations in speech and different algorithms have been proposed for the exploitation of modulations i...
It is well known that utterances convey a great deal of information about the speaker in addition to their semantic content. One such type of information consists of cues to the s...
One of the biggest challenges in speaker recognition is dealing with speaker-emotion variability. The basic problem is how to train the emotion GMMs of the speakers from their neu...
Pitch mismatch between training and testing is one of the important factors causing the performance degradation of the speaker recognition system. In this paper, we adopted the mis...
The Gaussian Mixture Model (GMM) is often used in conjunction with Mel-frequency cepstral coefficient (MFCC) feature vectors for speaker recognition. A great challenge is to use ...