The images of spectrogram analysis between the real and fake voices seemed to be distinguishable by the human eye. Can a image model be trained to detect fake voice spectrograms based on pitch and tone choppiness?
I find the site decently fast, definitely ugly but then again I don't want it to get a reddit-style redesign either. The information density is ok right now, and I'm actually impressed by the wide range of functionalities they have, related to reviewing books and updating your progress.
Working closely with people (friends preferably) who have higher "discipline" than you, and seeing how they grind their way through a problem is instructive sometimes.
I've seen something similar in some extremist bot accounts, where the tweet picture and text has a titillating and sexual tone (like catfishing) but includes an unrelated political hashtag at the end. These bots try to get certain hashtags trending without the users who fav the tweets realizing that.
What's your age? I've noticed in my circle that single unmarried people have less pressing things to do after work, thus are open to working in the weekends, unlike people with families.
Why generate a fake story? Why not communicate the real and moving journey of how a single note in the training data travelled through hundreds of neurons and thousands of matrices, and eventually made it past the final activation function to become a feature in the output tensor.