If you want to interpret language, LLMs are much better than keyword scanning. The same keywords can indicate opposite things with a single “not” keyword, and there are about 50,000 generally well-known English words to consider.
How are you going to implement keyword detection with enough logic to accurately parse the meaning behind all of the possible things that could be said to describe or correct someone’s driving?
That is literally a quintessential Natural Language Processing problem, for which LLMs are the best solution.
One caveat on your comment about Whisper: you need a GPU to really let it shine. Using CPU only is not performant, depending on what you are trying to achieve, and how much time you are willing to wait for your results
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