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Fingerprinting to Identify Repeated Sound Events in Long-Duration Personal Audio Recordings

Ogle, James P.; Ellis, Daniel P. W.

Body-worn audio recorders can collect huge "personal audio" archives of everything heard by the user, but navigating this data is a challenge. We investigate a noise-resistant audio fingerprint as a way to identify recurrent sound events. The fingerprint works well for data that is highly repeatable (e.g. phone rings) but not for more "organic" sounds (door closures etc.).

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More About This Work

Academic Units
Electrical Engineering
Published Here
July 13, 2012

Notes

Presented at the IEEE International Conference on Acoustics, Speech, and Signal Processing, Honolulu, Hi., April 15-20, 2007.