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3 changes: 3 additions & 0 deletions egs/rm/s5/RESULTS
Original file line number Diff line number Diff line change
Expand Up @@ -229,6 +229,9 @@ for x in exp/nnet2_online_wsj/nnet_ms_a_smbr_0.00005/1/decode_*; do grep WER $x/
%WER 7.33 [ 919 / 12533, 80 ins, 153 del, 686 sub ] exp/nnet2_online_wsj/nnet_ms_a_smbr_0.00005/1/decode_ug_epoch3/wer_13
%WER 7.36 [ 923 / 12533, 85 ins, 148 del, 690 sub ] exp/nnet2_online_wsj/nnet_ms_a_smbr_0.00005/1/decode_ug_epoch4/wer_13

### chain results ###
# current best chain result with TDNN (check local/chain/run_tdnn_5f.sh)
%WER 2.94 [ 369 / 12533, 51 ins, 71 del, 247 sub ] exp/chain/tdnn_5f/decode/wer_3_0.5

### nnet1 results ###

Expand Down
131 changes: 131 additions & 0 deletions egs/rm/s5/local/chain/run_tdnn_5f.sh
Original file line number Diff line number Diff line change
@@ -0,0 +1,131 @@
#!/bin/bash

# this script is a modified version of swbd/run_tdnn_5f.sh

set -e

# configs for 'chain'
stage=0
train_stage=-10
get_egs_stage=-10
dir=exp/chain/tdnn_5f

# training options
num_epochs=12
initial_effective_lrate=0.005
final_effective_lrate=0.0005
leftmost_questions_truncate=-1
max_param_change=2.0
final_layer_normalize_target=0.5
num_jobs_initial=2
num_jobs_final=4
minibatch_size=128
frames_per_eg=150
remove_egs=false

# End configuration section.
echo "$0 $@" # Print the command line for logging

. cmd.sh
. ./path.sh
. ./utils/parse_options.sh

if ! cuda-compiled; then
cat <<EOF && exit 1
This script is intended to be used with GPUs but you have not compiled Kaldi with CUDA
If you want to use GPUs (and have them), go to src/, and configure and make on a machine
where "nvcc" is installed.
EOF
fi

# The iVector-extraction and feature-dumping parts are the same as the standard
# nnet2 setup, and you can skip them by setting "--stage 4" if you have already
# run those things.

ali_dir=exp/tri3b_ali
treedir=exp/chain/tri4_2y_tree
lang=data/lang_chain_2y

local/online/run_nnet2_common.sh --stage $stage || exit 1;

if [ $stage -le 4 ]; then
# Get the alignments as lattices (gives the CTC training more freedom).
# use the same num-jobs as the alignments
nj=$(cat exp/tri3b_ali/num_jobs) || exit 1;
steps/align_fmllr_lats.sh --nj $nj --cmd "$train_cmd -l q=all.q" data/train \
data/lang exp/tri3b exp/tri3b_lats
rm exp/tri3b_lats/fsts.*.gz # save space
fi

if [ $stage -le 5 ]; 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
# topology.
steps/nnet3/chain/gen_topo.py $nonsilphonelist $silphonelist >$lang/topo
fi

if [ $stage -le 6 ]; then
# Build a tree using our new topology.
steps/nnet3/chain/build_tree.sh --frame-subsampling-factor 3 \
--leftmost-questions-truncate $leftmost_questions_truncate \
--cmd "$train_cmd -l q=all.q" 1200 data/train $lang $ali_dir $treedir
fi

if [ $stage -le 7 ]; then
steps/nnet3/chain/train_tdnn.sh --stage $train_stage \
--xent-regularize 0.1 \
--leaky-hmm-coefficient 0.1 \
--l2-regularize 0.00005 \
--jesus-opts "--jesus-forward-input-dim 200 --jesus-forward-output-dim 500 --jesus-hidden-dim 2000 --jesus-stddev-scale 0.2 --final-layer-learning-rate-factor 0.25" \
--splice-indexes "-1,0,1 -2,-1,0,1 -3,0,3 -6,-3,0" \
--apply-deriv-weights false \
--frames-per-iter 1000000 \
--lm-opts "--num-extra-lm-states=200" \
--get-egs-stage $get_egs_stage \
--minibatch-size $minibatch_size \
--egs-opts "--frames-overlap-per-eg 0" \
--frames-per-eg $frames_per_eg \
--num-epochs $num_epochs --num-jobs-initial $num_jobs_initial --num-jobs-final $num_jobs_final \
--feat-type raw \
--online-ivector-dir exp/nnet2_online/ivectors \
--cmvn-opts "--norm-means=false --norm-vars=false" \
--initial-effective-lrate $initial_effective_lrate --final-effective-lrate $final_effective_lrate \
--max-param-change $max_param_change \
--cmd "$decode_cmd" \
--remove-egs $remove_egs \
data/train $treedir exp/tri3b_lats $dir || exit 1;
fi

if [ $stage -le 8 ]; then
steps/online/nnet2/extract_ivectors_online.sh --cmd "$train_cmd" --nj 4 \
data/test exp/nnet2_online/extractor exp/nnet2_online/ivectors_test || exit 1;
fi

if [ $stage -le 9 ]; then
# Note: it might appear that this $lang directory is mismatched, and it is as
# far as the 'topo' is concerned, but this script doesn't read the 'topo' from
# the lang directory.
utils/mkgraph.sh --self-loop-scale 1.0 data/lang $dir $dir/graph
steps/nnet3/decode.sh --acwt 1.0 --post-decode-acwt 10.0 \
--extra-left-context 20 --scoring-opts "--min-lmwt 1" \
--nj 20 --cmd "$decode_cmd" \
--online-ivector-dir exp/nnet2_online/ivectors_test \
$dir/graph data/test $dir/decode || exit 1;
fi

if [ $stage -le 10 ]; then
utils/mkgraph.sh --self-loop-scale 1.0 data/lang_ug $dir $dir/graph_ug
steps/nnet3/decode.sh --acwt 1.0 --post-decode-acwt 10.0 \
--extra-left-context 20 \
--nj 20 --cmd "$decode_cmd" \
--online-ivector-dir exp/nnet2_online/ivectors_test \
$dir/graph_ug data/test $dir/decode_ug || exit 1;
fi
wait;
exit 0;