Hi, I would approach this by
- converting as much as possible of your text snippets into a neutral (information only) tone, sort of stripping your language style. This would give you the “common style denominator” format.
- Train a model to convert text from this “common style denominator” back to your style language.
Then when you need to “translate” style from one person to yours, you do it in two steps:
- You convert their text to neutral style first to keep the information only.
- You use your model to convert the neutral text into your tone.
Why? This way you avoid all the issues of the original tone messing up with your tone during the translation. And also it is easier to train a general model to strip style from any narrator to a common neutral style and then convert it to a specific tone, than training models to do conversion between many possible pairs of styles…
Let me know how it goes, interested in results.
As for the chat bot - make sure you understand the concept of fact embedding / retrieval (check my previous posts for details).