Virtual fusion for speaker recognition

Study of Applicability of Virtual Users in Evaluating Multimodal Biometrics

A new approach of enlarging fused biometric databases is presented. Fusion strategies based upon matching score are applied on active biometrics verification scenarios. Consistent biometric data of two traits are used in test scenarios of handwriting and speaker verification. The fusion strategies are applied on multimodal biometrics of two different user types. The real users represent two bio...

Speaker Independent Speech Recognition Using Hidden Markov Models for Persian Isolated Words

Speaker Adaptation in Continuous Speech Recognition Using MLLR-Based MAP Estimation

A variety of methods are used for speaker adaptation in speech recognition. In some techniques, such as MAP estimation, only the models with available training data are updated. Hence, large amounts of training data are required in order to have significant recognition improvements. In some others, such as MLLR, where several general transformations are applied to model clusters, the results ar...

Speaker Independent Speech Recognition Using Hidden Markov Models for Persian Isolated Words

Applying Score Reliability Fusion to Bi-Model Emotional Speaker Recognition

Emotion mismatch between training and testing is one of the important factors causing the performance degradation of speaker recognition system. In our previous work, a bi-model emotion speaker recognition (BESR) method based on virtual HD (High Different from neutral, with large pitch offset) speech synthesizing was proposed to deal with this problem. It enhanced the system performance under m...