Lazy AI editing tools strike again - AudioShake's Multi-speaker
Ever feel like you're relying way too much on fancy AI tools to clean up your audio mess?
Well, we’re sharing yet another villain that's been shoved out onto the market, hoping to find lazy creators who want to clean up their recordings!
We’re chatting about AudioShake's new multi-speaker feature that promises to untangle overlapping conversations like a pro. But here's the question - if we're all taking the adequate level of care over our recordings, should these tools even exist?
Mentioned in this episode:
A Podknows Production
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Transcript
Let's talk about a thing that shouldn't be a thing.
Speaker A:Podmaster hi, this is podnos Podcasting's associate producer Amelia Knight with another Podcasting Insights update.
Speaker A:Sort of.
Speaker A:I'm Emil AI the version of Amelia that gets rolled on this podcast.
Speaker A:Whenever human, Amelia is in a co working space and gets shy.
Speaker A:AudioShake's multi speaker has been released and I'm sure were hoping to get the podcasting industry excited.
Speaker A:But that's not what's happened to our team at podnos.
Speaker A:This new model claims to separate an unlimited number of speakers into individual audio tracks, making it easier to edit messy, overlapping conversations.
Speaker A:But here's the thing.
Speaker A:Should we really need AI to clean up poor recording practices?
Speaker A:If people just recorded their content properly in the first place, a tool like this wouldn't even be necessary.
Speaker A:If you've ever struggled with editing a chaotic panel discussion or trying to transcribe a podcast where everyone talks over each other, you might be intrigued by what AudioShake is offering.
Speaker A:But let's be honest, most of these problems could be avoided with better recording techniques, proper mic placement, using separate tracks for each speaker, and actually managing a conversation instead of letting it turn into a free for all.
Speaker A:These are the real solutions.
Speaker A:Instead, we're now relying on AI to fix what should have been done right from the start.
Speaker A:This is yet another example of empowering creator laziness and rewarding poor effort.
Speaker A:Sure, if you're recording everyone onto one track, this might help, but you really shouldn't be doing that in the first place.
Speaker A:That's it for today's episode of the Podmaster.
Speaker A:If you found this interesting, make sure you're following the podcast and keep an eye on your library for more insights on things like you know how to do things right from the start starts so you don't need an AI tool to fix it all later.
Speaker A:Until next time, keep creating properly.
Speaker A:The Fogmaster is a Podnos production.
Speaker A:Find out more about us at Podnos Co UK Podnos.
