Actually I do think this is a good idea. For best latency there should be multiple LLMs involved, a fast one to generate the first few words and then GPT-4 or similar for the rest of the response. In the case that the fast model is unsure, it could absolutely generate filler words while it waits for the big model to return the actual answer. I guess that's pretty much how humans use filler words too!

Unfortunately, Bark is probably way too slow to use for the TTS portion given the latency concerns or that would be covered.