How does Kaldi ASR compare with Mozilla DeepSpeech in terms of the speech recognition accuracy (e.g., in terms of word error rate)?

2 Answers 2


https://web.archive.org/web/20171130080859/https://hacks.mozilla.org/2017/11/a-journey-to-10-word-error-rate/ :

Our word error rate on LibriSpeech’s test-clean set is 6.5%, which not only achieves our initial goal, but gets us close to human level performance. [...] (5.83% according to the Deep Speech 2 paper). On a MacBook Pro, using the GPU, the model can do inference at a real-time factor of around 0.3x, and around 1.4x on the CPU alone. (A real-time factor of 1x means you can transcribe 1 second of audio in 1 second.)

Bonus: Facebook AI Research Automatic Speech Recognition Toolkit (Torch+lua, BSD License) gets 4.8% WER test-clean and 14.5% WER test-other on the LibriSpeech corpus.

  • Since you found the answer, you could mark your own answer as "accepted". Otherwise, the question will keep getting bumped to the front page by SE bots.
    – prash
    Commented Dec 30, 2017 at 12:42
  • @prash Good point, done Commented Jan 1, 2018 at 8:26
  • WER is not the only parameter we should be measuring how one ASR library fares against the other, a few other parameters can be: how good they fare in noisy scenarios, how easy is it to add vocabulary, what is the real-time factor, how robustly the trained model responds to changes in accent intonation etc.
    – absin
    Commented Feb 19, 2019 at 4:03
  • @AbSin 100% agreed. Commented Feb 19, 2019 at 4:04

Kaldi provides WER of 4.28% whereas deepspeech gives 5.83% on librispeech clean data. Check this out: https://github.com/syhw/wer_are_we

  • 2
    Thanks, it's not Mozilla DeepSpeech though, but Baidu's :/ Commented Nov 23, 2017 at 17:46

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