Yep, we use deep learning to generate an index of audio features and an approximate search to look through it all. We've done lots of testing on both clear and average/noisy audio. With standard transcription matching you get ~alright results (50% retrieval) on clear audio but really terrible results on average/noisy audio (<20% retrieval). With deepgram you get great results on clear audio (90% retrieval) and still really good results (80% retrieval) on noisy/average quality content.

We're always trying to make the indexing and search better/faster. For Hoogley we had to pull some tricks to get the search to be really fast for a lot of users, so it isn't quite as high quality as it can be. Working on it though ;)