Hi there,
My name is Reuben, I’m a radiology resident from Melbourne Australia.
I’ve built a “Dictation Error Corrector” web app using text-davinci-003 to address I problem I and many radiologists have.
As you can see in the example above, “enostoses” has been changed to “osteochondromas”. This is not correct, and unfortunately continues to recur in my experience using the app. There are a number of other similar mistakes that continue to be made (“enlocated” becomes “encumbered / encompassed / ensured”). Presumably, the model has not seen a great deal of these specific words in its training corpus.
My prompt is very simple, and I have found that if I specify “permitted words” in the prompt the resulting output is less reliable.
I feel as though this problem could be solved with fine-tuning, however davinci is so much worse than text-davinci-003 at a base level.
Any thoughts on how I might be able to solve this dilemma 
Thanks 