Biometric Authentication: A Machine Learning Approach

9.6. Speaker Verification Based on Articulatory Features

Most traditional speaker verification systems are based on the modeling of short-term spectral information [306]. These systems compute the ratio of the likelihood of the genuine speaker model to the likelihood of the impostor model given some spectral features extracted from a claimant. The resulting likelihood ratio is compared against a threshold for decision making. The advantage of using short-term spectral information is that promising results are obtainable from a limited amount of training data. However, spectral information is only one of many sources suitable for speaker verification. For example, in addition to the spectral information, humans make use of high-level information, ...