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So it worked quite well, with negligible perceived lag!
-wraith808 (January 02, 2021, 10:04 PM)
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Great, thanks for the details.

I used USB Camera Pro - Connect EasyCap or USB WebCam
-wraith808 (January 02, 2021, 10:04 PM)
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Good find. Though this is such a neat way to reuse old devices that I wish Google adds its own USB webcam functionality for it to Android. Also wishing Raspberry Pi OS came with some send-HDMI-over-USB functionality to make the converter hardware redundant.

The microphone line I hear most often recommended is the Blue Yeti.

I am looking to buy myself a good microphone as I want to start streaming, which one would you actually recommend me, or in case there is anyone who is streaming in here, which microphone are you using?
-Liamer (January 15, 2021, 09:36 AM)
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Not for live-streaming (but I could), I use a selection of Zingyou (Chinese) Condensor Microphones + a Behringer (u-phoria um2) interface (to provide 48v power and physical gain control).  I know people don't usually recommend Chinese stuff, but honestly, these microphones I got were both super cheap (<£50 each), came with everything they needed (telescopic arm, leads, pop filter, etc) and I have had 0 problems with a single one of them!

I'd highly recommend a telescopic arm for your microphone + a good pop filter!

Also, as for software, a mixture of Voicemeeter and CARLA (for VST plugins/effects) should be more than enough.

I finally fixed the Bluetooth issues on my laptop, once and for all, with this:


It's not just a solution, it's also a nice, inexpensive upgrade to BT 5.0. :)

It seems to have a slightly shorter range than my built-in Bluetooth, though, so my headphones start cutting out on the far side of my kitchen. I can't listen to music while cleaning my bathroom or making a sandwich. But it will do for now, since it lets me use my Bluetooth mouse without any problems.

Something new in my quest to turn my RasPi into SkyNet: Coral Accelerator


The Coral USB Accelerator adds an Edge TPU coprocessor to your system, enabling high-speed machine learning inferencing on a wide range of systems, simply by connecting it to a USB port.


The on-board Edge TPU coprocessor is capable of performing 4 trillion operations (tera-operations) per second (TOPS), using 0.5 watts for each TOPS (2 TOPS per watt).
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