Forensic Voice Comparisons in German with Phonetic and Automatic Features Using Vocalise Software

Jesse M, Alexander A, Forth O. Forensic Voice Comparisons in German with Phonetic and Automatic Features Using Vocalise Software. In: AES Conference: 54th International Conference: Audio Forensics. Audio Engineering Society; 2014. Paper 2-2. Available from: https://aes.org/publications/elibrary-page/?id=17328

@inproceedings{Jesse2014_17328,
  author = {Jesse, Michael and Alexander, Anil and Forth, Oscar},
  title = {{Forensic Voice Comparisons in German with Phonetic and Automatic Features Using Vocalise Software}},
  booktitle = {AES Conference: 54th International Conference: Audio Forensics},
  note = {Paper 2-2},
  year = {2014},
  month = jun,
  publisher = {Audio Engineering Society},
  url = {https://aes.org/publications/elibrary-page/?id=17328}
}

TY  - CPAPER
TI  - Forensic Voice Comparisons in German with Phonetic and Automatic Features Using Vocalise Software
AU  - Jesse, Michael
AU  - Alexander, Anil
AU  - Forth, Oscar
T2  - AES Conference: 54th International Conference: Audio Forensics
M1  - Paper 2-2
PY  - 2014
DA  - 2014/06/06
UR  - https://aes.org/publications/elibrary-page/?id=17328
PB  - Audio Engineering Society
LA  - en
AB  - In this article, we present a novel forensic speaker recognition system that provides the capability to perform comparisons using both ‘traditional’ forensic phonetic parameters and ‘automatic’ spectral features in a semi- or fully automatic way. We evaluate this approach with simulated and real forensic case data in German, which ranges from high quality laboratory audio data to real telephone intercepts. We examine how the forensic expert can use his or her knowledge of the linguistic and phonetic content of the speech and combine it with ‘automatic’ acoustic analysis of the speech. This approach is shown to provide a level of validation and safeguard against misleading or incorrect identification results. We demonstrate that processing phonetic data will be in many ways complementary and will offer insights into the voice comparison analysis that the classical automatic methods cannot.
ER  -