Logical evaluation of evidence when a person is suspected of committing two separate offences.

We consider the problem of drawing inferences within a legal framework when a person is a suspect for two separate offences. Although we are primarily concerned with scientific evidence the issue inevitably arises as to how that evidence interacts with other, non-scientific evidence. We show that, in this particular context, the evidence can be conveniently classified into three categories that concern, respectively: the first crime only; the second crime only; and evidence that relates to similarities between the two crimes. Two case examples are considered and we consider DNA, fibres and eyewitness evidence. These are viewed from the perspective of a prosecutor who has to decide whether or not to charge a suspect with one or both crimes. Graphical sensivity analyses are presented which have features that are not intuitively obvious.     

Introducing a semi-automatic method to simulate large numbers of forensic fingermarks for research on fingerprint identification

Statistical research on fingerprint identification and the testing of automated fingerprint identification system (AFIS) performances require large numbers of forensic fingermarks. These fingermarks are rarely available. This study presents a semi-automatic method to create simulated fingermarks in large quantities that model minutiae features or images of forensic fingermarks. This method takes into account several aspects contributing to the variability of forensic fingermarks such as the number of minutiae, the finger region, and the elastic deformation of the skin. To investigate the applicability of the simulated fingermarks, fingermarks have been simulated with 5-12 minutiae originating from different finger regions for six fingers. An AFIS matching algorithm was used to obtain similarity scores for comparisons between the minutiae configurations of fingerprints and the minutiae configurations of simulated and forensic fingermarks. The results showed similar scores for both types of fingermarks suggesting that the simulated fingermarks are good substitutes for forensic fingermarks.     

Performance Study of a Score‐based Likelihood Ratio System for Forensic Fingermark Comparison

In this article, the performance of a score‐based likelihood ratio (LR) system for comparisons of fingerprints with fingermarks is studied. The system is based on an automated fingerprint identification system (AFIS) comparison algorithm and focuses on fingerprint comparisons where the fingermarks contain 6–11 minutiae. The hypotheses under consideration are evaluated at the level of the person, not the finger. The LRs are presented with bootstrap intervals indicating the sampling uncertainty involved. Several aspects of the performance are measured: leave‐one‐out cross‐validation is applied, and rates of misleading evidence are studied in two ways. A simulation study is performed to study the coverage of the bootstrap intervals. The results indicate that the evidential strength for same source comparisons that do not meet the Dutch twelve‐point standard may be substantial. The methods used can be generalized to measure the performance of score‐based LR systems in other fields of forensic science.     

语音分析

导言在斯坦利·库布里克的经典电影《2001太空漫游》中(1968出品),男主人公可以通过发出声音通过关卡。科幻小说以及日常生活中闻声识人的经验,使人们认为话者。①识别无论对人还是对机器都是业已解决了的问题。     

Computation of likelihood ratios in fingerprint identification for configurations of three minutiae

Recent challenges to fingerprint evidence have brought forward the need for peer-reviewed scientific publications to support the evidential value assessment of fingerprint. This paper proposes some research directions to gather statistical knowledge of the within-source and between-sources variability of configurations of three minutiae on fingermarks and fingerprints. This paper proposes the use of the likelihood ratio (LR) approach to assess the value of fingerprint evidence. The model explores the statistical contribution of configurations of three minutiae using Tippett plots and related measures to assess the quality of the system. Features vectors used for statistical analysis have been obtained following a preprocessing step based on Gabor filtering and image processing to extract minutia position, type, and direction. Spatial relationships have been coded using Delaunay triangulation. The metric, used to assess similarity between two feature vectors is based on an Euclidean distance measure. The within-source variability has been estimated using a sample of 216 fingerprints from four fingers (two donors). Between-sources variability takes advantage of a database of 818 ulnar loops from randomly selected males. The results show that the data-driven approach adopted here is robust. The magnitude of LRs obtained under the prosecution and defense propositions stresses upon the major evidential contribution that small portions of fingermark, containing three minutiae, can provide regardless of its position on the general pattern.     

Consensus on validation of forensic voice comparison

Since the 1960s, there have been calls for forensic voice comparison to be empirically validated under casework conditions. Since around 2000, there have been an increasing number of researchers and practitioners who conduct forensic-voice-comparison research and casework within the likelihood-ratio framework. In recent years, this community of researchers and practitioners has made substantial progress toward validation under casework conditions becoming a standard part of practice: Procedures for conducting validation have been developed, along with graphics and metrics for representing the results, and an increasing number of papers are being published that include empirical validation of forensic-voice-comparison systems under conditions reflecting casework conditions. An outstanding question, however, is: In the context of a case, given the results of an empirical validation of a forensic-voice-comparison system, how can one decide whether the system is good enough for its output to be used in court? This paper provides a statement of consensus developed in response to this question. Contributors included individuals who had knowledge and experience of validating forensic-voice-comparison systems in research and/or casework contexts, and individuals who had actually presented validation results to courts. They also included individuals who could bring a legal perspective on these matters, and individuals with knowledge and experience of validation in forensic science more broadly. We provide recommendations on what practitioners should do when conducting evaluations and validations, and what they should present to the court. Although our focus is explicitly on forensic voice comparison, we hope that this contribution will be of interest to an audience concerned with validation in forensic science more broadly. Although not written specifically for a legal audience, we hope that this contribution will still be of interest to lawyers.