Steps to reproduce results on WSJ

Run data and auxiliary files (like lexicon, tokens set, etc.) preparation (set necessary paths instead of [...]: data_dst path to data to store, model_dst path to auxiliary path to store, kenlm path to prepare language model for decoding; if you are using B-version of WSJ then call with --wsj1_type LDC94S13B)

python3 prepare.py --wsj0 [...]/csr_1 --wsj1 [...]/csr_2_comp --wsj1_type LDC94S13A \
  --data_dst [...] --model_dst [...]  --sph2pipe [...]/sph2pipe_v2.5/sph2pipe --kenlm [...]

Besides data the auxiliary files for acoustic and language models training/evaluation will be generated:

cd $MODEL_DST
tree -L 2
.
├── am
│   ├── lexicon_si284+nov93dev.txt
│   └── tokens.txt
└── decoder
    ├── lexicon.txt # it is combination of words from si284 and lm text data
    ├── lm-4g.arpa
    └── lm-4g.bin

To run training/decoding:

Fix the paths inside *.cfg
Run training with train.cfg
Run decoding with decode*.cfg