面向执法机构的突破性说话人识别方法:SIIP

2017 European Intelligence and Security Informatics Conference (EISIC) Pub Date : 2017-09-01 DOI:10.1109/EISIC.2017.14

Khaled Khelif, Yann Mombrun, G. Backfried, Farhan Sahito, L. Scarpato, P. Motlícek, S. Madikeri, Damien Kelly, Gideon Hazzani, Emmanouil Chatzigavriil

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引用次数: 8

摘要

本文介绍了SIIP(说话人识别集成项目)，一个高性能的创新和可持续的说话人识别(SID)解决方案，运行在大型语音样本数据库上。该解决方案基于一系列语音分析算法的开发、集成和融合，包括说话人模型识别、性别识别、年龄识别、语言和口音识别、关键词和分类识别。提出了一个完整的集成系统，确保多源数据管理、先进的语音分析、信息共享和高效一致的人机交互。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Towards a Breakthrough Speaker Identification Approach for Law Enforcement Agencies: SIIP

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 solution is based on development, integration and fusion of a series of speech analytic algorithms which includes speaker model recognition, gender identification, age identification, language and accent identification, 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.

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2017 European Intelligence and Security Informatics Conference (EISIC)

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