zlacker

>>illumi+(OP)
This is very impressive.

I'm the owner of Broadcastify.com, where presumably these streams are being transcribed from. We've dabbled in this space and looked at real-world approaches to taking something like this to market, but transcribing 7000+ streams to text seems like an expensive (computational) and ($$) effort that needs a lot of investigation.

Note to mention that the individual lexicons between streams are drastically different.

I wonder how the developer has done the integration to our streams... because I never heard from them :)

>>blanto+G2
You could conceivably do this using the text to speech recognition on a Mac using Loopback to capture the stream to a microphone input.

https://rogueamoeba.com/loopback/

Someone clever enough could create containers to run the software locally and have many loops running off many streams to many instances of the audio to text feature.

>>godzil+W6
Accuracy is a little wonky even with real speech to text toolkits like Kaldi (which I’ll mention is a pain to even get started with it).

I’ve had some decent results with the following:

https://cmusphinx.github.io/

I have to research how to hand tag my own samples to see if that offers significant accuracy improvements (let’s say I want to accurately transcribe one voice consistently).

Google and Watson APIs are not too free, and I believe Watson has a audio length limit (possibly limited by free tier, or possibly limited in general for all tiers).

Cool to see some real world attempts using this stuff.