Summary of the paper

Title FABIOLE, a Speech Database for Forensic Speaker Comparison
Authors Moez Ajili, Jean-françois Bonastre, Juliette Kahn, Solange Rossato and Guillaume Bernard
Abstract A speech database has been collected for use to highlight the importance of “speaker factor” in forensic voice comparison. FABIOLE has been created during the FABIOLE project funded by the French Research Agency (ANR) from 2013 to 2016. This corpus consists in more than 3 thousands excerpts spoken by 130 French native male speakers. The speakers are divided into two categories: 30 target speakers who everyone has 100 excerpts and 100 “impostors” who everyone has only one excerpt. The data were collected from 10 different French radio and television shows where each utterance turns with a minimum duration of 30s and has a good speech quality. The data set is mainly used for investigating speaker factor in forensic voice comparison and interpreting some unsolved issue such as the relationship between speaker characteristics and system behavior. In this paper, we present FABIOLE database. Then, preliminary experiments are performed to evaluate the effect of the “speaker factor” and the show on a voice comparison system behavior.
Topics Corpus (Creation, Annotation, etc.), Speech Resource/Database, Person Identification
Full paper FABIOLE, a Speech Database for Forensic Speaker Comparison
Bibtex @InProceedings{AJILI16.35,
  author = {Moez Ajili and Jean-françois Bonastre and Juliette Kahn and Solange Rossato and Guillaume Bernard},
  title = {FABIOLE, a Speech Database for Forensic Speaker Comparison},
  booktitle = {Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC 2016)},
  year = {2016},
  month = {may},
  date = {23-28},
  location = {Portorož, Slovenia},
  editor = {Nicoletta Calzolari (Conference Chair) and Khalid Choukri and Thierry Declerck and Sara Goggi and Marko Grobelnik and Bente Maegaard and Joseph Mariani and Helene Mazo and Asuncion Moreno and Jan Odijk and Stelios Piperidis},
  publisher = {European Language Resources Association (ELRA)},
  address = {Paris, France},
  isbn = {978-2-9517408-9-1},
  language = {english}
 }
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