keveman

Moonshine author here: The warning is from Keras library, and is benign. If you didn't get any other output, it was probably because the model thought there was no speech (not saying there really was no speech). We uploaded ONNX version that is considerably faster than the Torch/JAX/TF versions, and is usable with less package bloat. I hope you would give it another shot.

This enables a true natural language voice interface to any device/appliance that currently has a touch pad or a bunch of buttons. Yes, faster than faster-whisper, but that's really an apples to oranges comparison, because useful-transformers uses the NPU on the Rockchip processors, so it works only on those. Whereas faster-whisper works fast on most/all platforms.

This is for speech to text, so generating text, not audio. And on a $120-$170 device, this transcribes at 30x real time. The code does run on lower end Rockchip processors, costing ~$30, although only at 10x real time speed.

The tiny.en Whisper model transcribes speech at 30x real-time speeds on an Orange Pi 5.

I met Bram in the Google Mountain View office. We chatted for over two hours. He was full of humility and curiosity and more interested in what I was working on (I was working on DistBelief back then). Hats off to a life full of impact and a legacy that will continue to impact programmers all over the world. RIP.

> How is this programmed?

Full disclosure: I am a Cerebras employee.

There is extensive support for TensorFlow. A wide range of models expressed in the TensorFlow will be accelerated transparently.