Dr. H. van den Heuvel studied German Language and Literature (main topic phonetics) in Utrecht. In 1996 he defended his PhD thesis entitled “Speaker variability in acoustic properties of Dutch phoneme realisations”. He co-ordinated the work on orthographic transcriptions in various projects for KPN, Philips, Temic, and CGN. Since 2001 he is managing director of SPEX and since 2003 of the Centre for Language and Speech Technology (CLST) at the Radboud University Nijmegen. One of CLST's research domains is forensic aspects of language and speech technology. Recent projects involve detection of threatening messages on the internet and bayesian modeling of biometric features such as speaker recognition (see http://bbfor2.net).The Bayesian framework of interpreting biometric evidence has several advantages. Firstly, it brings the two use cases in forensics closer together. In fact, the same technology can be used for the purpose of investigation and evidence, if the biometric can be shown to produce calibrated likelihoodratios. This can potentially make the investigation more effective as traces that help in finding a suspect of a crime can also serve as evidence. Secondly, we can use similar methodologies for the various biometrics for determining the calibrated likelihood ratio. Thirdly, we can combine multiple traces in different biometric modalities in the same framework.