Title :
Known-Audio Detection using Waveprint: Spectrogram Fingerprinting by Wavelet Hashing
Author :
Covell, Michele ; Baluja, Sanjeev
Author_Institution :
Google Inc., Mountain View, CA, USA
Abstract :
In this paper, we present a novel system for detecting known audio. We start with Waveprint, an audio identification system that, given a probe snippet, efficiently provides reliable forced-choice ranking of entries from an audio database. For open-set detection, we can re-examine the best-ranked matches from waveprint using simple temporal-ordering-based processing. The resulting system has excellent detection capabilities for small snippets of audio that have been degraded in a variety of manners, including competing noise, poor recording quality, and cell-phone playback. The system is more accurate than the previous state-of-the-art system while being more efficient and flexible in memory usage and computation.
Keywords :
audio coding; cryptography; audio detection; audio identification system; forced-choice ranking; memory usage; open-set detection; probe snippet; spectrogram fingerprinting; wavelet hashing; waveprint; Acoustic noise; Acoustic signal detection; Audio databases; Degradation; Fingerprint recognition; Image segmentation; Noise robustness; Probes; Spectrogram; Wavelet coefficients; Acoustic Applications; Acoustic Signal Detection; Music; Pattern Recognition;
Conference_Titel :
Acoustics, Speech and Signal Processing, 2007. ICASSP 2007. IEEE International Conference on
Conference_Location :
Honolulu, HI
Print_ISBN :
1-4244-0727-3
DOI :
10.1109/ICASSP.2007.366660