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

James P. Ogle; Daniel P. W. Ellis

Title:
Fingerprinting to Identify Repeated Sound Events in Long-Duration Personal Audio Recordings
Author(s):
Ogle, James P.
Ellis, Daniel P. W.
Date:
Type:
Presentations
Department:
Electrical Engineering
Permanent URL:
Notes:
Presented at the IEEE International Conference on Acoustics, Speech, and Signal Processing, Honolulu, Hi., April 15-20, 2007.
Abstract:
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.).
Subject(s):
Artificial intelligence
Electrical engineering
Item views:
35
Metadata:
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