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.
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?
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.
