4 ms·
So you are using a lower accuracy model and also a stripped down version of it. It might work for your domain but can't be generalizable. I have problem with pe
by master_yoda_1 6y ago
So you are using a lower accuracy model and also a stripped down version of it. It might work for your domain but can't be generalizable. I have problem with people who make a blanket statement about running model on CPU. Heck Yeh I can run an kaldi ASR engine on "Raspberry Pi", but not that accurate.
- whimsicalism 6y agoWhat a surprisingly condescending response, I thought you were genuinely curious. I never said anything about lower accuracy - we are running full size transformer models for translation. And wav2letter++ inference models are SOTA on the Librispeech leaderboards, so try again. This is a completely different architecture than Kaldi and, frankly, conflating the two is wrong. > have problem with people who make a blanket statement about running model on CPU. What was my "blanket statement"? I said that the statement "For some task inference CPU can't be real time... speech recognitions and friends, machine translation etc" was false, because those tasks can be done in real time on CPU. The original claim seems to be much more of a blanket statement than my response. Cheers.
- master_yoda_1 6y agoTry it "Zamia Speech: Open source state of the art speech recognition" https://www.raspberrypi.org/forums/viewtopic.php?t=216638 https://www.raspberrypi.org/forums/viewtopic.php?t=216638
- whimsicalism 6y agoWhat do you mean? I'm familiar with Kaldi - although haven't tried running it on an Rpi (nor with these particular models). That's materially different from w2l though.