7 ms·

On a different note, imagine the power of this for DRM control and censorship. But impressive and very useful.

nddrylliog 14y ago
What? What do speech recognition and fingerprinting have in common? I don't see how this research applies for DRM... Censorship, maybe. And even then, you can't filter conversations in real-time, only maybe 'flag' people with forbidden words.
- toemetoch 14y ago
  Pretty much all DRM content has unique patterns. Want to prohibit videos of the Starcraft game? Simple search for a few sentences like "more vespene gas" and "require more minerals". Want to find online copies of "Aliens"? Just enter a few catchphrases or part of a dialogue like "They come mostly at night. Mostly." And even then, you can't filter conversations in real-time, only maybe 'flag' people with forbidden words. Yes, that's really assuring to know it's not in real time.
  - lt 14y ago
    Those don't really require textual matching, just regular audio fingerprinting. In fact, doing that would match Starcraft or movies podcasts, where people are quoting the source.
    - toemetoch 14y ago
      With audio fingerprinting the content provider must provide a way to fingerprint its own audio and have access to fingerprints of the internet's audio/video. This means a partnership between e.g. youtube and a studio. I'm fairly sure this involves studios above a certain size, resources for programming+API and a fair bit of paperwork and testing for robustness as there are ways to mess with the technique. With this technique you just enter a few words and look at what comes out. You're suggesting that the first option is easier?
      - lt 14y ago
        Yes. Not only easier, but more reliable. The examples you gave are perfectly static sound bits - they don't change. It doesn't make sense to transcribe them to text, just match the audio. Soundhound/Shazam/etc do this easily. I'm pretty sure YouTube has some kind of similar mechanism already in place. This technology gets a lot more interesting if you want to search for people talking about you or your products.

What? What do speech recognition and fingerprinting have in common? I don't see how this research applies for DRM... Censorship, maybe. And even then, you can't filter conversations in real-time, only maybe 'flag' people with forbidden words.

toemetoch 14y ago
Pretty much all DRM content has unique patterns. Want to prohibit videos of the Starcraft game? Simple search for a few sentences like "more vespene gas" and "require more minerals". Want to find online copies of "Aliens"? Just enter a few catchphrases or part of a dialogue like "They come mostly at night. Mostly." And even then, you can't filter conversations in real-time, only maybe 'flag' people with forbidden words. Yes, that's really assuring to know it's not in real time.
- lt 14y ago
  Those don't really require textual matching, just regular audio fingerprinting. In fact, doing that would match Starcraft or movies podcasts, where people are quoting the source.
  - toemetoch 14y ago
    With audio fingerprinting the content provider must provide a way to fingerprint its own audio and have access to fingerprints of the internet's audio/video. This means a partnership between e.g. youtube and a studio. I'm fairly sure this involves studios above a certain size, resources for programming+API and a fair bit of paperwork and testing for robustness as there are ways to mess with the technique. With this technique you just enter a few words and look at what comes out. You're suggesting that the first option is easier?
    - lt 14y ago
      Yes. Not only easier, but more reliable. The examples you gave are perfectly static sound bits - they don't change. It doesn't make sense to transcribe them to text, just match the audio. Soundhound/Shazam/etc do this easily. I'm pretty sure YouTube has some kind of similar mechanism already in place. This technology gets a lot more interesting if you want to search for people talking about you or your products.