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* Using Shazam-like audio fingerprinting to block advertisements in audio podcasts | * Using Shazam-like audio fingerprinting to block advertisements in audio podcasts | ||
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Advertisement-blocking applications in internet browsers (e.g. AdBlock in Firefox or Chrome) block advertisements appearing on websites so that they do not display on screen. Audio fingerprinting applications like Shazam recognize a song from small segments by using audio fingerprinting. The objective of this thesis is to design a program which is able to block advertisements found on audio available for download on the web (podcast) on semi-supervised form. The method should exploit fingerprinting techniques like those of Shazam and the fact that Ads do not change from podcast to podcast, unlike the conventional content. The work will include | Advertisement-blocking applications in internet browsers (e.g. AdBlock in Firefox or Chrome) block advertisements appearing on websites so that they do not display on screen. Audio fingerprinting applications like Shazam recognize a song from small segments by using audio fingerprinting. The objective of this thesis is to design a program which is able to block advertisements found on audio available for download on the web (podcast) on semi-supervised form. The method should exploit fingerprinting techniques like those of Shazam and the fact that Ads do not change from podcast to podcast, unlike the conventional content. The work will include |
Advertisement-blocking applications in internet browsers (e.g. AdBlock in Firefox or Chrome) block advertisements appearing on websites so that they do not display on screen. Audio fingerprinting applications like Shazam recognize a song from small segments by using audio fingerprinting. The objective of this thesis is to design a program which is able to block advertisements found on audio available for download on the web (podcast) on semi-supervised form. The method should exploit fingerprinting techniques like those of Shazam and the fact that Ads do not change from podcast to podcast, unlike the conventional content. The work will include
- Gathering a small set of audio examples from the web containing advertisements (i.e. from BBC podcasts) which is representative of the problem to be solved.
- Using fingerprinting algorithms to identify similar segments in the audio podcasts, store fingerprints and filter out advertisements.