It looks like they used NIST's switchboard corpus, so it's an error rate for native language, and it's well-documented that it typically gets you around 5-6% er

It looks like they used NIST's switchboard corpus, so it's an error rate for native language, and it's well-documented that it typically gets you around 5-6% errors on human transcriptions, yep. However, it's worth remembering that this refers only to the transcription accuracy, i.e. mapping sound to a particular word in a permanent record (e.g. a written word, in a human transcriber's case). Humans can cope with error rates around 5% (and even higher) when recognizing words because we can use context to deduce the intended meaning, or ask for clarification when the word doesn't match the context. AI has some way to go until there. This isn't to say this is useless, quite the contrary. Being able to transcribe words in conversational language is hugely useful (for both nefarious and non-nefarious purposes). It's just that it refers to understanding the words, not the sentences :).