local/chain/run_tdnn.sh：

bash -x local/nnet3/run_ivector_common.sh --stage $stage || exit 1 
#展示了随机改变训练数据的倍速和音量来扩充多样性


if [ $stage -le 7 ]; then
  # Get the alignments as lattices (gives the LF-MMI training more freedom).
  # use the same num-jobs as the alignments把对齐作为词图文件
  nj=$(cat $ali_dir/num_jobs) || exit 1;
  steps/align_fmllr_lats.sh --nj $nj --cmd "$train_cmd" data/$train_set \
    data/lang exp/tri5a exp/tri5a_sp_lats
  rm exp/tri5a_sp_lats/fsts.*.gz # save space
fi
#下边一直到9看书P237
if [ $stage -le 8 ]; then
  # Create a version of the lang/ directory that has one state per phone in the
  # topo file. [note, it really has two states.. the first one is only repeated
  # once, the second one has zero or more repeats.]
  rm -rf $lang
  cp -r data/lang $lang
  silphonelist=$(cat $lang/phones/silence.csl) || exit 1;
  nonsilphonelist=$(cat $lang/phones/nonsilence.csl) || exit 1;
  # Use our special topology... note that later on may have to tune this
  #