The FLL Laboratory is concentrated on the development of semi-automatic and automatic systems for Forensic Voice Comparison. According to the Bayesian and Likelihood principle, we agree that the evaluation and presentation of evidence in the forensic sciences deal with the quantifiable properties of data from known and questioned origin (i.e. DNA, finger marks, etc.).
Recently, we developed the automatic software INTREPIDO. INTREPIDO provides the user with an operational environment for conducting forensic voice comparison, using an automated approach.
The primary users of the software are professionals in the investigative and judicial sectors: experts, technical consultants, personnel from judicial police, and law enforcement officers in general.
In its current version, INTREPIDO relies on the extraction of voice recording features known as “embeddings,” through a component implementing an ECAPA-TDNN neural network (Emphasized Channel Attention, Propagation and Aggregation – Time Delay Neural Network). The characteristics of this neural network are described in Desplanques et al. (2020). The first international publication applying this neural network to forensic voice comparison is by the authors: Sigona & Grimaldi (2024): https://doi.org/10.1016/j.specom.2024.103045.
The most commonly used evaluation metrics to describe system performance include both numerical and graphical metrics. The numerical metrics considered are the following (cf. Brümmer & du Preez, 2006; van Leeuwen & Brümmer, 2007; González-Rodríguez et al., 2007; Morrison, 2011; Drygajlo et al., 2015; Meuwly et al., 2017):
For further information about the software: impavido@biometriaforense.it
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