%Aigaion2 BibTeX export from Idiap Publications %Saturday 21 December 2024 06:08:49 PM @INPROCEEDINGS{Khelif_STO-MP-IST-160_2018, author = {Khelif, Khaled and yann Mombrun and Hazzani, Gideon and Motlicek, Petr and Madikeri, Srikanth and Sahito, Farhan and Kelly, Damien and Scarpatto, Luca and Chatzigavriil, Emmanouil and Backfried, Gerhard}, projects = {Idiap, SIIP}, month = may, title = {SIIP: An Innovative Speaker Identification Approach for Law Enforcement Agencies}, booktitle = {Big Data and Artificial Intelligence for Military Decision Making}, year = {2018}, pages = {PT-1 - 1: PT-1 - 14}, publisher = {STO}, organization = {http://www.sto.nato.int/}, note = {Meeting Proceedings RDP}, isbn = {ISBN 978-92-837-2181-9}, url = {https://www.sto.nato.int/publications/STO%20Meeting%20Proceedings/STO-MP-IST-160/MP-IST-160-PT-1.pdf}, doi = {10.14339/STO-MP-IST-160}, abstract = {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.} }