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Juliette Kahn

3 accepted papers

2018

ASR Performance Prediction on Unseen Broadcast Programs Using Convolutional Neural Networks

ICASSP 2018accepted

In this paper, we address a relatively new task: prediction of ASR performance on unseen broadcast programs. We first propose an heterogenous French corpus dedicated to this task. Two prediction approaches are compared: a state-of-the-art performance prediction based on regression (engineered featur…

Cited by 0SourceScholar
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