Can I use machine learning to automatically transcribe and summarize my audio lectures for better retention?

I totally get why you'd want to automate transcribing and summarizing your audio lectures - it can be a huge time-saver and help with retention. I've looked into this myself, and yeah, machine learning can definitely help with that. There are some pretty cool tools and platforms out there that use ML algorithms to transcribe and summarize audio recordings, like Otter or Trint.

From what I've seen, these tools can be pretty accurate, especially if you've got clear audio recordings. I'd recommend checking out Otter, it's specifically designed for lectures and meetings, and it's got some great features like automatic summarization and keyword extraction. You can also try out Trint, it's more geared towards podcasters and journalists, but it's got some really powerful transcription and summarization tools.

As for specific settings or parameters, I'd say it's worth experimenting with different options to see what works best for your recordings. For example, you might need to adjust the audio quality settings or the summarization length to get the best results. I'd also recommend checking out the documentation for whichever tool you choose, they usually have some great tips and tricks for getting the most out of their ML algorithms.

Overall, I think machine learning can be a huge help with transcribing and summarizing your audio lectures, and it's definitely worth giving it a shot. I hope this helps, and good luck with your studies - I know how tough it can be to keep up with a heavy course load! If you've got any more questions or need further recommendations, feel free to ask.