## Abstract

Logistic-regression calibration and fusion are potential steps in the calculation of forensic likelihood ratios. The present paper provides a tutorial on logistic-regression calibration and fusion at a practical conceptual level with minimal mathematical complexity. A score is log-likelihood-ratio like in that it indicates the degree of similarity of a pair of samples while taking into consideration their typicality with respect to a model of the relevant population. A higher-valued score provides more support for the same-origin hypothesis over the different-origin hypothesis than does a lower-valued score; however, the absolute values of scores are not interpretable as log likelihood ratios. Logistic-regression calibration is a procedure for converting scores to log likelihood ratios, and logistic-regression fusion is a procedure for converting parallel sets of scores from multiple forensic-comparison systems to log likelihood ratios. Logistic-regression calibration and fusion were developed for automatic speaker recognition and are popular in forensic voice comparison. They can also be applied in other branches of forensic science, a fingerprint/finger-mark example is provided.

Original language | English |
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Pages (from-to) | 173-197 |

Number of pages | 25 |

Journal | Australian Journal of Forensic Sciences |

Volume | 45 |

Issue number | 2 |

DOIs | |

Publication status | Published - 1 Jun 2013 |

## Keywords

- Calibration
- Forensic science
- Fusion
- Likelihood ratio
- Logistic regression
- Score