IT
Speaker Recognition
Moez Ajili, Solange Rossato, Dan Zhang and Jean-François Bonastre
It is common to see voice recordings being presented as a forensic trace in court. Generally, a forensic expert is asked to analyse 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 thespeakers 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 is responsible of 2/3 the system loss. In this article, we wish to take our analysis a step farther and investigate deeper the intra-speaker variability based on rhythmic parameters. We focus on the impact of rhythmic parameters on FVC performance and variability, as changes in speaker speech rhythm...
Cite as: Ajili, M., Rossato, S., Zhang, D., Bonastre, J. (2018) Impact of rhythm on forensic voice comparison reliability. Proc. Odyssey 2018 The Speaker and Language Recognition Workshop, 1-8, DOI: 10.21437/Speaker Odyssey.2018-1.
Infos
- Emmanuelle Billard
- Oct. 16, 2018, midnight
- Conférence
- French