Sadly, Mozilla's effort is somewhat flawed in its current iteration. There are only very few different sentences (tokens) used as prompts, leading to a lot of r

Sadly, Mozilla's effort is somewhat flawed in its current iteration. There are only very few different sentences (tokens) used as prompts, leading to a lot of repetitions of the same spoken utterance instead of greater coverage of possible utterances, and there is near complete overlap in the sentences spoken in the training set and those in the development and test sets, making it nearly impossible to generalize results from performance evaluations to utterances not contained in the training set. See https://discourse.mozilla.org/t/common-voice-v1-corpus-design-problems-overlapping-train-test-dev-sentences/24288/2 https://discourse.mozilla.org/t/common-voice-v1-corpus-desig... Some suggestions for improvements were made in a discussion on the Kaldi Github (https://github.com/kaldi-asr/kaldi/issues/2141 https://github.com/kaldi-asr/kaldi/issues/2141), but the bottom line is that it's not clear what the exact use-case of the corpus is. It's not command recognition, there's no particular domain, just more or less random English sentences collected from CC0 sources. Use cases should drive corpus collection.