Yannick Estève / ONTRAC-Kaldi

Blame view

egs/wsj/s5/local/online/run_nnet2_common.sh 2.94 KB
edit raw normal view history
8dcb6dfcb   Yannick Estève   first commit 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
 
  #!/bin/bash
  
  # this script is called from scripts like run_nnet2.sh; it does
  # the common stages of the build.
  
  . ./cmd.sh
  mfccdir=mfcc
  
  stage=1
  
  . ./cmd.sh
  . ./path.sh
  . ./utils/parse_options.sh
  
  
  if [ $stage -le 1 ]; then
    for datadir in train_si284 test_eval93 test_dev93 test_eval92; do
      utils/copy_data_dir.sh data/$datadir data/${datadir}_hires
      steps/make_mfcc.sh --nj 40 --mfcc-config conf/mfcc_hires.conf \
        --cmd "$train_cmd" data/${datadir}_hires exp/make_hires/$datadir $mfccdir || exit 1;
      steps/compute_cmvn_stats.sh data/${datadir}_hires exp/make_hires/$datadir $mfccdir || exit 1;
    done
    utils/subset_data_dir.sh --first data/train_si284_hires 7138 data/train_si84_hires || exit 1
  fi
  
  
  if [ $stage -le 2 ]; then
    # We need to build a small system just because we need the LDA+MLLT transform
    # to train the diag-UBM on top of.  We align the si84 data for this purpose.
  
    steps/align_fmllr.sh --nj 40 --cmd "$train_cmd" \
      data/train_si84 data/lang exp/tri4b exp/nnet2_online/tri4b_ali_si84
  fi
  
  if [ $stage -le 3 ]; then
    # Train a small system just for its LDA+MLLT transform.  We use --num-iters 13
    # because after we get the transform (12th iter is the last), any further
    # training is pointless.
    steps/train_lda_mllt.sh --cmd "$train_cmd" --num-iters 13 \
      --realign-iters "" \
      --splice-opts "--left-context=3 --right-context=3" \
      5000 10000 data/train_si84_hires data/lang \
       exp/nnet2_online/tri4b_ali_si84 exp/nnet2_online/tri5b
  fi
  
  if [ $stage -le 4 ]; then
    mkdir -p exp/nnet2_online
  
    steps/online/nnet2/train_diag_ubm.sh --cmd "$train_cmd" --nj 30 \
       --num-frames 400000 data/train_si84_hires 256 exp/nnet2_online/tri5b exp/nnet2_online/diag_ubm
  fi
  
  if [ $stage -le 5 ]; then
    # even though $nj is just 10, each job uses multiple processes and threads.
    steps/online/nnet2/train_ivector_extractor.sh --cmd "$train_cmd" --nj 10 \
      data/train_si284_hires exp/nnet2_online/diag_ubm exp/nnet2_online/extractor || exit 1;
  fi
  
  if [ $stage -le 6 ]; then
    # We extract iVectors on all the train_si284 data, which will be what we
    # train the system on.
  
    # having a larger number of speakers is helpful for generalization, and to
    # handle per-utterance decoding well (iVector starts at zero).
    steps/online/nnet2/copy_data_dir.sh --utts-per-spk-max 2 data/train_si284_hires \
      data/train_si284_hires_max2
  
    steps/online/nnet2/extract_ivectors_online.sh --cmd "$train_cmd" --nj 30 \
      data/train_si284_hires_max2 exp/nnet2_online/extractor exp/nnet2_online/ivectors_train_si284 || exit 1;
  fi
  
  if [ $stage -le 7 ]; then
    rm exp/nnet2_online/.error 2>/dev/null
    for data in test_eval92 test_dev93 test_eval93; do
      steps/online/nnet2/extract_ivectors_online.sh --cmd "$train_cmd" --nj 8 \
        data/${data}_hires exp/nnet2_online/extractor exp/nnet2_online/ivectors_${data} || touch exp/nnet2_online/.error &
    done
    wait
    [ -f exp/nnet2_online/.error ] && echo "$0: error extracting iVectors." && exit 1;
  fi
  
  exit 0;