I need model that can just differentiate when someone is talking normaly or singing. Is there any trained AI that does that?

Comments

kduyehj t1_jah1cry wrote on March 1, 2023 at 11:20 AM

Maybe you don’t need a model. Try Fourier analysis to analyse in the frequency domain. Look at the distributions and do something like Kullback–Leibler divergence to measure your sample distribution against a singing-reference, and against a talking-reference.

Stencolino OP t1_jaj8ue6 wrote on March 1, 2023 at 8:48 PM

Thanks, ill think about it

keph_chacha t1_jag33wh wrote on March 1, 2023 at 4:22 AM

you can build one

Stencolino OP t1_jaj8jqw wrote on March 1, 2023 at 8:47 PM

I tought about it, it should be simple enough but I was just wondering if there was one already made

currentscurrents t1_jag9v2w wrote on March 1, 2023 at 5:24 AM

Can I? I don't have a cluster of 10x A100s.

All the interesting stuff in ML seems to require expensive hardware. I guess it'll be cool in 5-10 years when consumer hardware catches up.

[deleted] t1_jah7ias wrote on March 1, 2023 at 12:29 PM

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blablanonymous t1_jagadpr wrote on March 1, 2023 at 5:30 AM

I mean if you have a serious use case you can do it on cloud platforms. I imagine you could do some transfer learning or fine tuning using a pre trained model

currentscurrents t1_jagavxg wrote on March 1, 2023 at 5:35 AM

I can't afford to rent 10x A100s on cloud platforms for very long either,

Pretrained models are pretty great though. Most of my use cases are not particularly unique; models are the software libraries of the future.