The problem with that is that the language model's power is already used to fix things up locally (because this is transcribed from audio). As a result it can't be used again to decide if the transcription fits the model; it's the case by design. There must be some kind of confidence metric at the end of the process, but I don't think it's possible to tell how much of the ambiguity comes from inadequacies in the phoneme model, or the audio environment, or the language model. They'd have to throw out good transcriptions in noisy environments along with bad transcriptions, and probably wouldn't keep much at all. As it is it seems they prefer to publish crappy results and hopefully have some feedback channel involving the video uploader.