User verification: Matching the uploaders of videos across accounts

This article presents an attempt to link the uploaders of videos based on the audio track of the videos. Using a subset of the MediaEval [10] 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 recognition 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 recognition 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, security applications, and raises privacy concerns.

• Type: Journal
• Year: 2011
• Where: ICASSP
• Authors: Howard Lei, Jaeyoung Choi, Adam Janin, Gerald Friedland
• Keywords: Audio Track, Flickr Videos, ICASSP 2011, Signal Processing, Speaker Recognition