Robustness of forensic speaker verification systems based on Alize/Lia_Ral toolkit

Abstract

This paper presents the performance analysis of Alize/Lia_Ral algorithms in forensic speaker verification applications. In particular, in this work we evaluate the performance impact of speech signal degradation considering the background noise level, speech rate variation, audio signal length used for testing, GSM radio channel, etc. The Alize/Lia_Ral platform has demonstrated a strong dependence on the ambient noise and a slight dependence on Lombard effect, bandwidth reduction, length of the audio signal, and changes in speech rate.