Speaker identification and verification using Gaussian mixture speaker models
Speech Communication
Integrating Faces and Fingerprints for Personal Identification
IEEE Transactions on Pattern Analysis and Machine Intelligence
An overview of text-independent speaker recognition: From features to supervectors
Speech Communication
Speaker Verification Using Support Vector Machines and High-Level Features
IEEE Transactions on Audio, Speech, and Language Processing
A Cohort-Based Speaker Model Synthesis for Mismatched Channels in Speaker Verification
IEEE Transactions on Audio, Speech, and Language Processing
Robust Speaker Recognition in Noisy Conditions
IEEE Transactions on Audio, Speech, and Language Processing
Significance of Vowel-Like Regions for Speaker Verification Under Degraded Conditions
IEEE Transactions on Audio, Speech, and Language Processing
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In this paper an online text-independent speaker verification system developed at IIT Guwahati under multivariability condition for remote person authentication is described. The system is developed on a voice server accessible via telephone network using an interactive voice response (IVR) system in which both enrollment and testing can be done online. The speaker verification system is developed using Mel-Frequency Cepstral Coefficients (MFCC) for feature extraction and Gaussian Mixture Model--Universal Background Model (GMM-UBM) for modeling. The performance of the system under multi-variable condition is evaluated using online enrollments and testing from the subjects. The evaluation of the system helps in understanding the impact of several well known issues related to speaker verification such as the effect of environment noise, duration of test speech, robustness of the system against playing recorded speech etc. in an online system scenario. These issues need to be taken care for the development and deployment of speaker verification system in real life applications.