Prevalent speaker recognition methods use only spectralenvelope based features such as MFCC, ignoring the rich speaker identity information contained in the temporalspectral dynamics of the entire speech signal. We propose a new feature called compressed spectral dynamics or CSD for speaker recognition based on a compressed time-frequency representations of spoken passwords which effectively ca...

The problem of text-independent speaker recognition based on the use of vocal tract and residue signal LPC parameters is investigated. Pseudostationary segments of voiced sounds are used for feature selection. Parameters of the linear prediction model (LPC) of vocal tract and residue signal or LPC derived cepstral parameters are used as features for speaker recognition. Speaker identification i...

One major source of performance decline in speaker recognition system is channel mismatch between training and testing. This paper focuses on improving channel robustness of speaker recognition system in two aspects of channel compensation technique and channel robust features. The system is text-independent speaker identification system based on two-stage recognition. In the aspect of channel ...

Speaker recognition is the process of recognizing the speaker based on characteristics such as pitch, tone in the speech wave.Background noise influences the overall efficiency of speaker recognition system and is still considered as one of the most challenging issue in Speaker Recognition System (SRS). Support Vector Machine (SVM) and Hidden Markov Model (HMM) are widely used techniques for sp...

This paper proposes a new robust bi-modal audio visual speech and speaker recognition system by lip-motion and speech biometrics. To increase the robustness of speech and speaker recognition, we have proposed a method using speaker lip motion information extracted from video sequences with low resolution (128 ×128 pixels). In this paper we investigate a biometric system for speech recognition a...