Okay, so yesterday I was messing around, right? Just bored and scrolling through YouTube, and I stumbled upon some Family Guy clips. Chris Griffin, man, that dude is hilarious in a messed-up way. That got me thinking… could I train a basic AI to, like, talk like him?
First thing’s first: Data. I needed a bunch of Chris Griffin lines. So, I spent a good hour or two just ripping audio clips from YouTube. I wasn’t aiming for perfection, just quantity. Ended up with a folder full of short .wav files. Messy, but it was a start.
Next up, I needed to transcribe that stuff. Ain’t nobody got time to type all that out by hand. Found some free online speech-to-text tools. They weren’t great, tons of errors, especially with the weird stuff Chris says, but it gave me a decent base. Spent another hour or so cleaning up the transcripts, fixing the obvious mistakes. It was tedious.
Now for the “AI” part. I’m no machine learning guru, alright? So, I went the super simple route. I used a Markov chain. Basically, it looks at the words Chris uses and how often they follow each other. Then, it just spits out new sentences based on those probabilities. Think auto-complete, but dumber.
I used Python for this, because, well, everyone uses Python. Found a bunch of Markov chain libraries online. Picked one that looked easy to use. Tossed in my transcribed Chris Griffin lines. Hit “go.”
The results? Oh man, it was a disaster at first. Just complete gibberish. “Uh… couch… potato… Stewie… fart… Brian… huh?” But after tweaking the parameters a bit – like, how many words to look back when predicting the next word – it started to get a little better. Still nonsensical, but occasionally a sentence would pop out that sounded vaguely Chris-like.
Example output: “Gee, that’s kinda like a big, talking dog, Brian.” Or, “Darn it, Lois, where’s my mayonnaise?”
See? Almost there. It’s all about volume of training data. The more lines from chris, the better!
To improve, I think next steps would be:
- Getting better transcripts (maybe pay for a transcription service?)
- Adding more data (gotta find more Chris Griffin clips!)
- Trying a more sophisticated AI model (maybe something with actual learning involved)
But for a quick and dirty project? I’m pretty happy with it. It’s dumb, it’s silly, but it’s Chris Griffin-esque. And it only took me an afternoon. Maybe I’ll try Peter Griffin next time…
Anyway, that was my day. Hope you got a laugh out of it. I know I did.
