Long‐term changes in voice characteristics: Implications for speaker identity verification (SIV)

Abstract

In a typical speaker identity verification (SIV) scenario, a talker first asserts an identity claim via some means other than speech. A reference sample of the claimed individual's speech is then loaded into a pattern matcher and compared against a new sample of the same word or phrase solicited on‐line. Based on the similarity of the two utterances, and a predetermined criterion, a decision is made as to the veracity of the claimed identity. One difficult problem for SIV applications is that the spectral characteristics of a speaker's voice change over time in ways that are poorly understood. Utterances were collected from three speakers at regular intervals over a period of 23 weeks, and were analyzed first with respect to the magnitude of spectral dissimilarity over varying time intervals, and, second, with respect to the effect of these differences on error rates for an SIV decision task. The data show an increase in mean utterance dissimilarity of about 8% over a period of 2 weeks, followed by a much more gradual increase over 6 months. While the absolute change in mean dissimilarity was small, it resulted in a doubling of the error rate for the SIV decision task from about 5% to 10%.In a typical speaker identity verification (SIV) scenario, a talker first asserts an identity claim via some means other than speech. A reference sample of the claimed individual's speech is then loaded into a pattern matcher and compared against a new sample of the same word or phrase solicited on‐line. Based on the similarity of the two utterances, and a predetermined criterion, a decision is made as to the veracity of the claimed identity. One difficult problem for SIV applications is that the spectral characteristics of a speaker's voice change over time in ways that are poorly understood. Utterances were collected from three speakers at regular intervals over a period of 23 weeks, and were analyzed first with respect to the magnitude of spectral dissimilarity over varying time intervals, and, second, with respect to the effect of these differences on error rates for an SIV decision task. The data show an increase in mean utterance dissimilarity of about 8% over a period of 2 weeks, followed by a much...