Marijn Huijbregts
ABSTRACT
In this paper we discuss the challenges of scaling a speaker retrieval system for small audiovisual collections towards a speaker retrieval system for large audio (visual) archives. We show that with our large scale speaker diarization approach it is possible to perform query-by-example speaker retrieval; to search for audiovisual documents in which a particular person is talking. On a selection of the ICSI meeting corpus we obtain a Mean Average Precision of 0.49 and precision-at-ten of 0.70. On a much larger archive of three months of Dutch broadcast television we obtain a precision-at-ten of 0.52.
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Digital Library
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- M. Huijbregts and D. van Leeuwen. The RU submission to the Evalita'09 "application track" speaker recognition evaluation. In proceedings of Evalita 2009, 2009.Google Scholar
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- M. Huijbregts, C. Wooters, and R. Ordelman. Filtering the unknown: Speech activity detection in heterogeneous video collections. In proceedings of Interspeech, Antwerp, Belgium, August 2007.Google Scholar
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- D. van Leeuwen and M. Huijbregts. The AMI speaker diarization system for NIST RT06s meeting data. In (MLMI), volume 4299 of Lecture Notes in Computer Science, pages 371--384, Berlin, October 2007. Google ScholarDigital Library
- C. Wooters and M. Huijbregts. The ICSI RT07s speaker diarization system. In Multimodal Technologies for Perception of Humans, Lecture Notes in Computer Science, Berlin, 2008. Springer Verlag. Google ScholarDigital Library
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Index Terms
- Towards automatic speaker retrieval for large multimedia archives
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