CONF Khelif_STO-MP-IST-160_2018/IDIAP SIIP: An Innovative Speaker Identification Approach for Law Enforcement Agencies Khelif, Khaled yann Mombrun, Hazzani, Gideon Motlicek, Petr Madikeri, Srikanth Sahito, Farhan Kelly, Damien Scarpatto, Luca Chatzigavriil, Emmanouil Backfried, Gerhard http://www.sto.nato.int/ - Big Data and Artificial Intelligence for Military Decision Making 2018 STO PT-1 - 1: PT-1 - 14 ISBN 978-92-837-2181-9 Meeting Proceedings RDP https://www.sto.nato.int/publications/STO%20Meeting%20Proceedings/STO-MP-IST-160/MP-IST-160-PT-1.pdf URL 10.14339/STO-MP-IST-160 doi This paper describes SIIP (Speaker Identification Integrated Project) a high performance innovative and sustainable Speaker Identification (SID) solution, running over large voice samples database. The proposed solution is based on development, integration and fusion of a series of individual speech analytic algorithms which includes speaker recognition, gender/age/language/accent identification, large vocabulary multilingual automatic speech-to-text transcription, expanded by keyword and taxonomy spotting. A full integrated system is proposed ensuring multisource data management, advanced voice analysis, information sharing and efficient and consistent man-machine interactions. The implemented system presented in this paper has been introduced to the international community of law-enforcement agencies animated by Interpol. Preliminary feedbacks collected from end-users indicate their satisfaction with the proposed architecture and its functionality. They also expressed different exploitation needs that we will try to take into account in a further work.