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Would feeding the resultant recognized text into an LLM to have it correct the remaining mistakes be useful? Essentially to repair the transcription?

I did that with Whisper output and it helped improve a podcast transcription and logically inserted proper line spacing.



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I recently witnessed a speech in Indonesia for Nyepi, the Balinese New Year. I was trying to use Google Translate's live conversation feature to get an idea of what was being said. I still couldn't make out much more than "he's saying something about the importance of the holiday and being pure".

I pasted the auto-translation into ChatGPT and asked it to summarize:

> The speaker seems to be discussing the importance of Nyepi, a Balinese Day of Silence. They mention that happiness, peace, and prosperity can be achieved by being in harmony with space and time. The speaker also references ogoh-ogoh, which are statues symbolizing negative influences, and the Panca Maha Bhuta, or the five elements of life. They suggest that negative emotions and behaviors can lead to a "darkness of the mind."

> The speaker emphasizes the importance of self-control and using the Nyepi celebration as a milestone for personal growth. They mention the parading of the ogoh-ogoh, which represents negative behaviors being confronted and released. Following the Nyepi celebration, people should aim for a new and better life, leaving behind their past negative behaviors and emotions.

I'm not convinced of the accuracy, but I'd definitely say it's useful.


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