8 ms·
Check out `whisper` and `whisper-cpp` for ASR. I am running the smaller models in near real-time on a 3rd gen i7, with good results even using my terrible buil
by m2024 3y ago
Check out `whisper` and `whisper-cpp` for ASR.
I am running the smaller models in near real-time on a 3rd gen i7, with good results even using my terrible built-in laptop mic from a distance. The medium and large models are impressively accurate for technical language.
- jamil7 3y agoWhisper is for STT though right?
- qwertox 3y agoThe term STT is not used, it's called ASR, Automatic Speech Recognition. I mean, I was referring to both TTS and ASR in my comment.
- ametrau 3y agoNot used by who? It’s a better term. Let’s use it.
- m2024 3y agoI also use STT but the parent poster wrote ASR so for clarity I responded in kind.
- qwertox 3y agoI'm using Whisper to transcribe notes I record with a lavalier mic during my bike rides (wind is no problem), but am using OpenAI's service. When it was released I tested it on a Ryzen 5950x and it was too slow and memory hungry for my taste. Using large was necessary for that use case (also, I'm recording in German).
- GaggiX 3y agoWith Whisper, you can find many smaller models that are fine-tuned for a particular language, so even smaller models can perform adequately.
- kkielhofner 3y agoThe original release was full precision model weights running in an old version of PyTorch with no optimizations. Fast forward to now and you have faster-whisper (using Ctranslate2) and distil-whisper optimized weights. Between the two of them Whisper Large uses something like 1/8th the memory and is likely at least an order of magnitude faster on your hardware. German has no effect on these metrics and for accuracy it actually has a lower word error rate than English.