Publication Details
Title: Persona Linking: Matching Uploaders of Videos Across Accounts
Author: H. Lei, J. Choi, A. Janin, and G. Friedland
Group: ICSI Technical Reports
Date: October 20, 2010
PDF: http://www.icsi.berkeley.edu/pubs/techreports/TR-10-009.pdf
Overview:
This article presents an approach to link the uploaders of videos based on the audio track of the videos. Using a subset of the MediaEval Placing Task's Flickr video set, which is labeled with the uploader's name, we conducted an experiment with a similar setup as a typical NIST speaker identification evaluation run. Based on the assumption that the audio might be matched in various ways (speaker, channel, environmental noise, etc.), we trained one of ICSI's simplified speaker identification systems on the audio tracks of the Flickr videos. Note that since the selection of videos is essentially random, the audio track can contain any sounds. We obtain an equal error rate of 36.7% on 312 videos with 11,550 trials. The result has implications for audio research and security applications, and raises privacy concerns.
Acknowledgements:
This work was partially supported by funding provided to ICSI by NGA NURI grant #HM11582-10-1-0008.
Bibliographic Information:
ICSI Technical Report TR-10-009. Also appears in the proceedings of the International Conference on Acoustics, Speech and Signal Processing (ICASSP 2011), Prague, Czech Republic, May 2011.
Bibliographic Reference:
H. Lei, J. Choi, A. Janin, and G. Friedland. Persona Linking: Matching Uploaders of Videos Across Accounts. ICSI Technical Report TR-10-009. Also appears in the proceedings of the International Conference on Acoustics, Speech and Signal Processing (ICASSP 2011), Prague, Czech Republic, May 2011., October 20, 2010
Author: H. Lei, J. Choi, A. Janin, and G. Friedland
Group: ICSI Technical Reports
Date: October 20, 2010
PDF: http://www.icsi.berkeley.edu/pubs/techreports/TR-10-009.pdf
Overview:
This article presents an approach to link the uploaders of videos based on the audio track of the videos. Using a subset of the MediaEval Placing Task's Flickr video set, which is labeled with the uploader's name, we conducted an experiment with a similar setup as a typical NIST speaker identification evaluation run. Based on the assumption that the audio might be matched in various ways (speaker, channel, environmental noise, etc.), we trained one of ICSI's simplified speaker identification systems on the audio tracks of the Flickr videos. Note that since the selection of videos is essentially random, the audio track can contain any sounds. We obtain an equal error rate of 36.7% on 312 videos with 11,550 trials. The result has implications for audio research and security applications, and raises privacy concerns.
Acknowledgements:
This work was partially supported by funding provided to ICSI by NGA NURI grant #HM11582-10-1-0008.
Bibliographic Information:
ICSI Technical Report TR-10-009. Also appears in the proceedings of the International Conference on Acoustics, Speech and Signal Processing (ICASSP 2011), Prague, Czech Republic, May 2011.
Bibliographic Reference:
H. Lei, J. Choi, A. Janin, and G. Friedland. Persona Linking: Matching Uploaders of Videos Across Accounts. ICSI Technical Report TR-10-009. Also appears in the proceedings of the International Conference on Acoustics, Speech and Signal Processing (ICASSP 2011), Prague, Czech Republic, May 2011., October 20, 2010