Hey all - I made this and am wondering if anyone here has any experience with pocketsphinx and could lend a hand in making the transcriptions more accurate. Let me know! (Or just make a pull request.)
I second the opinion that Kaldi is more advanced, but it is also way, way more complicated to do anything with a custom dataset. There are a few examples of decoding with existing models though, so maybe that is a start. These lectures may help: http://www.danielpovey.com/kaldi-lectures.html
There is also an interesting toolbox here that you can train, though getting access to TIMIT, WSJ, etc. is pretty annoying. http://www.cs.cmu.edu/~ymiao/kaldipdnn.html
You may also get mileage out of some kind of post-transcription NLP/cleaning if you haven't done that yet.
Existing trained models can be downloaded from here: http://www.kaldi-asr.org/ (via: http://www.openslr.org/12/ http://www.clsp.jhu.edu/~guoguo/papers/icassp2015_librispeec...)