Publication Details
ROXSD: The ROXANNE Multimodal and Simulated Dataset for Advancing Criminal Investigations
DIKICI, E.
Madikeri Srikanth
RANGAPPA, P.
Backfried Gerhard
Rohdin Johan Andréas, M.Sc., Ph.D. (DCGM)
Schwarz Petr, Ing., Ph.D. (DCGM)
Kováč Marek, Ing.
Malý Květoslav, Ing.
Boboš Dominik, Ing.
KLAKOW, D.
Sergidou Eleni Konstantina
and others
Multimodal and Simulated Dataset, Advancing Criminal Investigations
The ROXANNE project, conducted under the European
Union's Horizon 2020 Programme, aimed to revolutionize
criminal investigations by integrating speech, language, and
video technologies with criminal network analysis. Despite the
success in technology development, the project faced evaluation
challenges due to the scarcity and legal restrictions surround-
ing real-world criminal activity datasets. In response, we intro-
duce ROXSD, a simulated dataset of communication in orga-
nized crime. ROXSD is a set of wiretapped conversations (col-
lected through communication service providers) between drug
dealing suspects, following a realistic screenplay (incl. realis-
tic conditions and constraints of a real investigation) prepared
by Law Enforcement Agencies (LEAs). With a focus on multi-
modality and multilinguality, the dataset comprises 20 hours of
telephone and video conversations involving 104 speakers, and
is further aligned with ground-truth annotations for each modal-
ity involved, enabling precise evaluation and development of
technologies. In addition, the multimodal data are enhanced
with metadata and prior knowledge (e.g., suspects' biometric
profiles) which is typically available as a result of lawfully in-
tercepted communication. This paper introduces ROXSD as a
pivotal resource for advancing technology in criminal research
(specifically in domain of speech, text and network analysis).
ROXSD not only facilitates in the domain of technology devel-
opment and evaluation but also showcases the potential of sim-
ulated datasets in advancing the field of organized crime analyt-
ics, emphasizing the importance of such datasets in the absence
of comprehensive real-world alternatives.
@inproceedings{BUT193433,
author="MOTLÍČEK, P. and DIKICI, E. and MADIKERI, S. and RANGAPPA, P. and BACKFRIED, G. and ROHDIN, J. and SCHWARZ, P. and KOVÁČ, M. and MALÝ, K. and BOBOŠ, D. and KLAKOW, D. and SERGIDOU, E.",
title="ROXSD: The ROXANNE Multimodal and Simulated Dataset for Advancing Criminal Investigations",
booktitle="Proceedings of Odyssey 2024: The Speaker and Language Recognition Workshop",
year="2024",
pages="17--24",
publisher="International Speech Communication Association",
address="Québec City",
doi="10.21437/odyssey.2024-3",
url="https://www.isca-archive.org/odyssey_2024/motlicek24_odyssey.pdf"
}