Impact of rhythm on forensic voice comparison reliability

Moez Ajili (1) , Solange Rossato (2) , Dan Zhang (2) , Jean-François Bonastre (1)

1 LIA - Laboratoire Informatique d'Avignon
2 GETALP - Groupe d’Étude en Traduction Automatique/Traitement Automatisé des Langues et de la Parole

It is common to see voice recordings being presented as a forensic trace in court. Generally, a forensic expert is asked to analyze both suspect and criminals voice samples in order to indicate whether the evidence supports the prosecution (same-speaker) or defence (different-speakers) hypotheses. This process is known as Forensic Voice Comparison (FVC). Since the emergence of the DNA typing model, the likelihood-ratio (LR) framework has become the new golden standard in forensic sciences. The LR not only supports one of the hypotheses but also quantifies the strength of its support. However, the LR accepts some practical limitations due to its estimation process itself. It is particularly true when Automatic Speaker Recognition (ASpR) systems are considered as they are outputting a score in all situations regardless of the case specific conditions. Indeed, several factors are not taken into account by the estimation process like the quality and quantity of information in both voice recordings, their phonological content or also the speakers intrinsic characteristics, etc. All these factors put into question the validity and reliability of FVC. In our recent study, we showed that intra-speaker variability explains 2/3 of the system losses. In this article, we investigate the relations between intra-speaker variability and rhythmic parameters.

Mots clés: Forensic voice comparison; rhythm; reliability; speaker factor; speaker recognition

Domaines: Informatique et langage [cs.CL]; Linguistique

Moez Ajili, Solange Rossato, Dan Zhang, Jean-François Bonastre. Impact of rhythm on forensic voice comparison reliability. Odyssey 2018 The Speaker and Language Recognition Workshop, Jun 2018, Les Sables d’Olonne, France. ⟨hal-01962531⟩