4 ms·

If Mozilla’s DeepSpeech is getting a 30% WER on this test set with a >2GB model... something is very wrong.

• kenarsa 8y ago
  This is a bit of surprise to me as well. That being said. The dataset is a tough one. I am ESL, but some of the accented examples I have a hard time understanding. Also the recordings are not near field and there is sometime some background noise.
  • p1esk 8y ago
    What is the WER of your model on Librispeech?
    • kenarsa 8y ago
      We used entire librispeech as part of our training set.
      • p1esk 8y ago
        Until you publish Librispeech WER for your model, it's pointless to discuss any advances in efficiency. I have no clue if your results on CommonVoice are good or bad.
• deleted 8y ago
  [deleted]
• glup 8y ago
  In my experience DeepSpeech with the default Mozilla model + 5-gram is extremely sensitive to background noise. Fiddling with the hyperparameters, e.g. upweighting the language model, helps a little.
  • kenarsa 8y ago
    Thanks. Do you use the default parameters and tune from there?