Waveprint: Efficient wavelet-based audio fingerprinting

Pattern Recognition

Volumn 41, Issue 11, 2008, Pages 3467-3480

  Baluja, Shumeet ^a   Covell, Michele ^a  

^a GOOGLE INC   (United States)

Author keywords

Applications; Audio retrieval; Image video retrieval; Pattern analysis

Indexed keywords

AUDIO SYSTEMS; COMPUTER HARDWARE DESCRIPTION LANGUAGES; COMPUTER SYSTEMS; COPYRIGHTS; DATA PROCESSING; DATA STORAGE EQUIPMENT; ELECTRIC BREAKDOWN; MOBILE TELECOMMUNICATION SYSTEMS; TELEPHONE SYSTEMS; TELEVISION APPLICATIONS;

AUDIO DATA; AUDIO FINGERPRINTING; AUDIO IDENTIFICATION; AUDIO SOURCES; CELL PHONES; COMPUTER-VISION; COPYRIGHT PROTECTIONS; LARGE-SCALE DATA; MEMORY USAGE; NOVEL METHODS; STATE OF THE ARTS; STREAM PROCESSING;

AUDIO ACOUSTICS;

EID: 48349143474     PISSN: 00313203     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.patcog.2008.05.006     Document Type: Article

References (34)

1. Gracenote Press Release, Gracenote global media 〈http://www.gracenote.com〉, 2006.
2. Shazam, Shazam entertainment limited 〈http://www.shazam.com/〉, 2006.
3. Google Video Team, About Google Video 〈http://video.google.com/video_about.html〉, 2005.
4. YouTube Press Release, YouTube opens Internet Video to the Masses 〈http://www.youtube.com/press_room_entry?entry=OcN9xXYar1g〉, 2005.
5. M. Fink, M. Covell, S. Baluja, Social- and interactive-television applications based on real-time ambient-audio identification, in: EuroITV, 2006.
6. M. Covell, S. Baluja, M. Fink, Advertisement replacement using acoustic and visual repetition, in: IEEE Multimedia Signal Proceedings, 2006.
7. J.S. Seo, J. Haitsma, T. Kalker, Linear speed-change resilient audio fingerprinting, in: Proceedings of IEEE Workshop on Model Based Processing and Coding of Audio, MPCA-2002, 2002.
8. Foosic, libFooID Free Fingerprinting Library 〈http://foosic.org/libfooid.php〉, 2008.
9. MusicBrainz, Picard, the next generation Musicbrainz tagger 〈http://musicbrainz.org/doc/PicardTagger〉, 2008.
10. Y. Ke, D. Hoiem, R. Sukthankar, Computer vision for music identification, in: Proceedings of Computer Vision and Pattern Recognition 2005, pp. 597-604.
11. S. Baluja, M. Covell, Audio fingerprinting: combining computer vision & data stream processing, in: Proceedings of the 2007 International Conference on Acoustics, Speech, and Signal Processing, 2007.
12. P. Cano, E. Batlle, E. Gomez, L. Gomes, M. Bonnet, Audio fingerprinting: concepts and applications, in: Studies in Computational Intelligence (SCI), vol. 2, 2005, pp. 233-245.
13. P. Cano, E. Batlle, T. Kalker, J. Haitsma, A review of algorithms for audio fingerprinting, in: International Workshop on Multimedia Signal Processing, 2002.
14. Audible Magic, Music and video identification empowers online media service providers 〈http://www.audiblemagic.com/products-services/contentsvcs/〉, 2008.
15. Barcelona Music and Audio Technologies, Match: track every bit of sound 〈http://www.bmat.com/match〉, 2007.
16. Gracenote, Gracenote Mobile Music Identification 〈http://www.gracenote.com/business_solutions/mobileMusic/〉, 2008.
17. Mediaguide, Mediaguide technology 〈http://www.mediaguide.com/technology/〉, 2008.
18. J. Haitsma, T. Kalker, A highly robust audio fingerprinting system, in: Proceedings of International Conference on Music Information Retrieval, 2002.
19. P. Viola, M. Jones, Robust real-time object detection, in: Proceedings of the CVPR, 2001.
20. C. Burges, J. Platt, S. Jana, Extracting noise-robust features from audio data, in: ICASSP, 2002.
21. Burges C., Platt J., and Jana S. Distortion discriminant analysis for audio fingerprinting. IEEE Trans. Speech & Audio Processing 11 3 (2003) 165-174
22. C. Jacobs, A. Finkelstein, D. Salesin, Fast multiresolution image querying, in: Proceedings of SIGGRAPH 95, 1995.
23. Deller Jr. J., Hansen J., and Proakis J. Discrete-Time Processing of Speech Signals (1999), Wiley, IEEE Press, New York
24. Stollnitz E., DeRose T., and Salesin D. Wavelets for computer graphics: a primer part I. IEEE Comput. Graphics Appl. 15 3 (1995) 76-84
25. Cohen E., Datar M., Fujiwara S., Gionis A., Indyk P., Motwani R., Ullman J.D., and Yang C. Finding interesting associations without support pruning. Knowl. Data Eng. 13 1 (2001) 64-78
26. Gionis A., Indyk P., and Motwani R. Similarity search in high dimensions via hashing. VLDB J. (1999) 518-529
27. J. Carter, M. Wegman, Universal classes of hash functions, in: Proceedings of the Ninth ACM Symposium on Theory of Computing, 1977, pp. 106-112.
28. Myers C.S., and Rabiner L.R. A comparative study of several dynamic time-warping algorithms for connected word recognition. Bell Syst. Tech. J. 60 7 (1981) 1389-1409
29. . J. ACM 32 3 (1985) 505-536
30. Veldhuis R., and He H. Time-scale and pitch modifications of speech signals and resynthesis from the discrete short-time Fourier transform. Speech Commun. 18 (1996) 257-279
31. Cortes C., and Vapnik V. Support vector networks. Machine Learning 20 3 (1995) 273-297
32. Joachims T. Making large-scale SVM learning practical. In: Scholkopf B., Burges C., and Smola A. (Eds). Advances in Kernel Methods-Support Vector Learning (1999), MIT Press, Cambridge, MA
33. Vapnik V.N. The Nature of Statistical Learning Theory (1995), Springer, Berlin
34. Turk M., and Pentland A. Eigenfaces for recognition. J. Cognitive Neurosci. 3 1 (1991) 71-86