ASR = automatic speech recognition. I think this is the same as STT, speech to text?
It seems to want an NVidia GPU. I didn't look closely to find out if it can run usably without one. For me, usable might mean 10% of realtime, i.e. an overnight run on my old x86 box for 1 hour of transcription. Of course faster is always nice. YMMV.
Almost all ML models come with reference python code that will run on most architectures.
If you want an implementation optimized for a certain architecture the cost is between 10-30USD of opus tokens and is oneshottable: ("implement Nvidia nemotron 3.5 transcribe for the intel npu on this machine. Use the hf transformers implementation as reference. The finished artifact takes pcm on stdin and utf8 chunks on stdout".)
You can substitute your old intel CPU by modifying the prompt by replacing "intel npu" with "the target cou on this machine ... Your task is complete when the model decode performance is 80% of the memory read speed of this machine"