Earlier quoted context omitted.
And the German is “subtitles of [public broadcaster] for [content network], 2017 I'm not sure this is really overfitting, the network does exactly what the training data demands. According to the training data silence art the end transcribes to a copyright notice or subtitle credits
> I'm not sure this is really overfitting, the network does exactly what the training data demands. What do you think overfitting is, if not that?
But in this case the behavior seems to generalize over multiple languages, with the model choosing representative "outro silence" captions depending on the language. Which is consistent with the training data showing that outro silence is captioned.
If the model was generalizing perfectly it would show something like "[subtitle credits here]" but that'd be demanding a bit much.
Transcribing outro silence as silence despite the training data consistently transcribing outro silence differently from regular silence would be underfitting