> And then just do a cleanup pass with a cheap LLM
I am especially interested in this part. Could you please share the prompt you are using to instruct the LLM to clean up the dictation? Thanks in advance!
I am especially interested in this part. Could you please share the prompt you are using to instruct the LLM to clean up the dictation? Thanks in advance!
My prompt is pretty simple:
- Intro of the purpose (faithful, high-quality summaries of meeting transcripts useful for readers who did not attend the meeting)
- Some basic rules
- Summarize only what is actually said in the transcript.
- If a speaker's name isn't clear from the transcript, describe them generically (e.g. "a participant") rather than guessing
- If the transcript is a fragment or cuts off, say so rather than inventing a resolution
- Only state a causal or explanatory link between two facts (e.g. why someone is absent) if that link is clearly stated in the transcript
- Preserve relative time references precisely rather than flattening them. If a speaker says something will happen "in two hours" don't reword it as "today" or "same day"
- Maintain the original voice and framing to keep original intent
- Attempt to infer meeting attendance based on who actually spoke or was spoken to
- Prefer plain, direct sentences over compound or clever phrasing
- Respond directly with the summary. Do not preface it with phrases like "Here is a summary" or "Based on the transcript".
- A preferred structure for the summary, with examples
- An instruction to attempt correction of mis-transcribed words based on the included JSON configuration, but only if the certainty is high. If unsure, leave as-is, but add (spelling?) after the word to flag it.
- The JSON config as a string.