from my experience, when trained with the same data, kaldi is slightly better and with custom recipes adaptable to changing conditions.
deepspeech has way better documentation and is more developer friendly.
wav2letter seems to be the quickest.
i guess there is no real winner here ... depends what criteria are applied.
just an example, kaldi is a weird mixture of c++, python2, python3, shell scripts, java, perl. hard to oversee. deepspeech is python. wav2letter is an exe file.
I was under the impression DeepSpeech was native (C++), with bindings for Python and others. Personally I've used it with Node.js so far, and I couldn't see any dependencies on Python.
edit: I was talking client, you're talking training I guess.
just an example, kaldi is a weird mixture of c++, python2, python3, shell scripts, java, perl. hard to oversee. deepspeech is python. wav2letter is an exe file.