I think you are looking at a too narrowly defined avenue to achieve this effect. There are multiple avenues to train a model to do this. Most simply is a fine

I think you are looking at a too narrowly defined avenue to achieve this effect. There are multiple avenues to train a model to do this. Most simply is a finetune on training examples where the the internal monologue is constructed in a manner that precedes the <aloud> tag and provides additional reasoning before the output. I think there is also scope for pretraining with a mask to not attempt to predict (or ignore the loss, same thing) certain things in the stream. For example to give time codes into the data stream. The training could then have an awareness of the passing of time but would not generate time codes as a prediction. Time codes could then be injected into the context at inference time and it would be able to use that data.