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Towards methods for efficient access to spoken content in the AMI corpus

Jones, Gareth J.F. and Eskevich, Maria and Gyarmati, Ágnes (2010) Towards methods for efficient access to spoken content in the AMI corpus. In: the Workshop on Searching Spontaneous Conversational Speech at ACM Multimedia 2010 (SSCS '10), 29 Oct 2010, Florence, Italy.

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Increasing amounts of informal spoken content are being collected. This material does not have clearly defined document forms either in terms of structure or topical content, e.g. recordings of meetings, lectures and personal data sources. Automated search of this content poses challenges beyond retrieval of defined documents, including definition of search items and location of relevant content within them. While most existing work on speech search focused on clearly defined document units, in this paper we describe our initial investigation into search of meeting content using the AMI meeting collection. Manual and automated transcripts of meetings are first automatically segmented into topical units. A known-item search task is then performed using presentation slides from the meetings as search queries to locate relevant sections of the meetings. Query slides were selected corresponding to well recognised and poorly recognised spoken content, and randomly selected slides. Experimental results show that relevant items can be located with reasonable accuracy using a standard information retrieval approach, and that there is a clear relationship between automatic transcription accuracy and retrieval effectiveness.

Item Type:Conference or Workshop Item (Paper)
Event Type:Workshop
Uncontrolled Keywords:natural language processing;
Subjects:Computer Science > Information retrieval
DCU Faculties and Centres:Research Initiatives and Centres > Centre for Next Generation Localisation (CNGL)
Research Initiatives and Centres > National Centre for Language Technology (NCLT)
DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing
Publisher:Association for Computing Machinery
Official URL:
Copyright Information:© 2010 ACM
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
ID Code:16044
Deposited On:22 Jul 2011 14:21 by Shane Harper. Last Modified 22 Jul 2011 14:21

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