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Moez Ajili

3 accepted papers

2017

Phonological content impact on wrongful convictions in Forensic Voice Comparison context

ICASSP 2017accepted

Forensic Voice Comparison (FVC) is increasingly using the likelihood ratio (LR) in order to indicate whether the evidence supports the prosecution (same-speaker) or defender (different-speakers) hypotheses. Nevertheless, the LR accepts some practical limitations due both to its estimation process it…

Cited by 0SourceScholar
2016

Inter-speaker variability in forensic voice comparison: A preliminary evaluation

ICASSP 2016accepted

In forensic voice comparison, it is strongly recommended to follow Bayesian paradigm. In this paradigm, the strength of the forensic evidence is summarized by a likelihood ratio (LR). The LR magnitude quantifies the strength of the evidence: far from unity for a meaningful LR (a LR which supports st…

Cited by 0SourceScholar
2015

Additive noise compensation in the i-vector space for speaker recognition

ICASSP 2015accepted

State-of-the-art speaker recognition systems performance degrades considerably in noisy environments even though they achieve very good results in clean conditions. In order to deal with this strong limitation, we aim in this work to remove the noisy part of an i-vector directly in the i-vector spac…

Cited by 0SourceScholar