How does Kaldi ASR compare with Mozilla DeepSpeech in terms of the speech recognition accuracy (e.g., in terms of word error rate)?
asked Oct 21, 2017 at 23:48
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2 Answers
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.
answered Nov 30, 2017 at 8:17
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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 ♦Dec 30, 2017 at 12:42
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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.– absinFeb 19, 2019 at 4:03
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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
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2Thanks, it's not Mozilla DeepSpeech though, but Baidu's :/ Nov 23, 2017 at 17:46