An investigation of speaker verification accuracy using fundamental frequency and duration as distinguishing features

A method of automatically verifying a person´s identity based on measurements of features taken from a sample of speech is presented. The design goal was to develop a simple, efficiently implemented system, compared with existing systems, while retaining as much accuracy as possible. Parameters extracted from the utterance are fundamental frequency of vocal cord vibration and duration of voicing. Mahalanobis and Euclidean distances are used to compare the sets of features. An accuracy of 100% was obtained for one individual with the Mahalanobis distance measure; several other individuals had performance accuracies over 90%. On the whole, accuracy rates achieved in the simulation were about 80%