4 ms·
I can't find exact numbers on Snips.ai, but generally there's a linear relation between the size of the inference model in RAM and the accuracy it can obtain.
by skoocda 9y ago
I can't find exact numbers on Snips.ai, but generally there's a linear relation between the size of the inference model in RAM and the accuracy it can obtain.
I'd have to assume DeepSpeech outperforms anything running on a RasPi3, at least for LVCSR. It hits 93.5% accuracy on Librispeech, which I've never seen from any offline recognition models.
- woodson 9y agoKaldi has 4.14% WER (95.86% accuracy) on the same test dataset (test-clean) [1] using a model that runs faster than real time on CPU. You would have to make the model smaller to run it in real time on a RasPi3, but according to this [2], you can get decent WERs for read speech even then. [1] https://github.com/kaldi-asr/kaldi/blob/master/egs/librispeech/s5/local/chain/tuning/run_tdnn_1b.sh https://github.com/kaldi-asr/kaldi/blob/master/egs/librispee... [2] https://groups.google.com/d/msg/kaldi-help/Pr6jPH1Qshg/kn8df0JmBQAJ https://groups.google.com/d/msg/kaldi-help/Pr6jPH1Qshg/kn8df...