[nddrylliog]

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]

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]

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]

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]

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.