Robust Automatic Speaker Diarisation of Audio Documents by Exploiting Prior Sources of Information

通过利用先前的信息源对音频文档进行鲁棒的自动说话人区分

• 批准号: LP0991238
• 负责人: Em/Prof Sridha Sridharan
• 金额: $ 21.05万
• 依托单位: Queensland University of Technology
• 依托单位国家: 澳大利亚
• 项目类别: Linkage Projects
• 财政年份: 2009
• 资助国家: 澳大利亚
• 起止时间: 2009-11-02 至 2012-12-31
• 项目状态: 已结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/LP0991238
• 关键词: Robust; Automatic; Speaker; Diarisation; Audio

Speaker Diarisation, the task of determining who spoke when, is a technology fundamental in deriving intelligent information from audio and multimedia resources. The requirement for efficient and accurate Speaker Diarisation systems, portable across different domains is heightened by the explosive growth of audio and multimedia archives online and throughout the world. This research will provide the foundation for a commercial service of automatic Speaker Diarisation to be developed, growing Australia's impact on the information and communications technology (ICT) sector. The outcome of this research will also assist in the tracking of terrorist and unlawful activity by enabling effective intelligence gathering from different audio sources.

扬声器识别，即确定谁在何时发言的任务，是从音频和多媒体资源中获取智能信息的一项技术基础。随着网上和世界各地音频和多媒体档案的爆炸性增长，人们对可跨不同领域携带的高效和准确的扬声器拨号系统的需求也越来越高。这项研究将为将要开发的自动扬声器拨号商业服务提供基础，增加澳大利亚对信息和通信技术(ICT)部门的影响。这项研究的结果还将有助于从不同的音频来源进行有效的情报收集，从而有助于追踪恐怖主义和非法活动。