Blame view
egs/chime4/s5_1ch/local/run_lmrescore.sh
4.13 KB
8dcb6dfcb
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 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 |
#!/bin/bash
# Copyright 2015 University of Sheffield (Jon Barker, Ricard Marxer)
# Inria (Emmanuel Vincent)
# Mitsubishi Electric Research Labs (Shinji Watanabe)
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
# Copyright 2015, Mitsubishi Electric Research Laboratories, MERL (Author: Takaaki Hori)
nj=12
stage=1
order=5
hidden=300
rnnweight=0.5
nbest=100
train=noisy
eval_flag=true # make it true when the evaluation data are released
. utils/parse_options.sh || exit 1;
. ./path.sh
. ./cmd.sh ## You'll want to change cmd.sh to something that will work on your system.
## This relates to the queue.
# This is a shell script, but it's recommended that you run the commands one by
# one by copying and pasting into the shell.
if [ $# -ne 2 ]; then
printf "
USAGE: %s <Chime4 root directory> <enhancement method>
" `basename $0`
echo "First argument specifies a root directory of Chime4 data"
echo "Second argument specifies a unique name for different enhancement method"
exit 1;
fi
# set language models
lm_suffix=${order}gkn_5k
rnnlm_suffix=rnnlm_5k_h${hidden}
# data root
chime4_data=$1
# enhan data
enhan=$2
# check data
if [ ! -d $chime4_data ]; then
echo "$chime4_data does not exist. Please specify chime4 data root correctly" && exit 1
fi
# check whether run_dnn is executed
srcdir=exp/tri4a_dnn_tr05_multi_${train}_smbr_i1lats
if [ ! -d $srcdir ]; then
echo "error, execute local/run_dnn.sh, first"
exit 1;
fi
# train a high-order n-gram language model
if [ $stage -le 1 ]; then
local/chime4_train_lms.sh $chime4_data || exit 1;
fi
# train a RNN language model
if [ $stage -le 2 ]; then
local/chime4_train_rnnlms.sh $chime4_data || exit 1;
fi
# preparation
dir=exp/tri4a_dnn_tr05_multi_${train}_smbr_lmrescore
mkdir -p $dir
# make a symbolic link to graph info
if [ ! -e $dir/graph_tgpr_5k ]; then
if [ ! -e exp/tri4a_dnn_tr05_multi_${train}/graph_tgpr_5k ]; then
echo "graph is missing, execute local/run_dnn.sh, correctly"
exit 1;
fi
pushd . ; cd $dir
ln -s ../tri4a_dnn_tr05_multi_${train}/graph_tgpr_5k .
popd
fi
# rescore lattices by a high-order N-gram
if [ $stage -le 3 ]; then
# check the best iteration
if [ ! -f $srcdir/log/best_wer_$enhan ]; then
echo "error, execute local/run_dnn.sh, first"
exit 1;
fi
it=`cut -f 1 -d" " $srcdir/log/best_wer_$enhan | awk -F'[_]' '{print $1}'`
# rescore lattices
if $eval_flag; then
tasks="dt05_simu dt05_real et05_simu et05_real"
else
tasks="dt05_simu dt05_real"
fi
for t in $tasks; do
steps/lmrescore.sh --mode 3 \
data/lang_test_tgpr_5k \
data/lang_test_${lm_suffix} \
data-fmllr-tri3b/${t}_$enhan \
$srcdir/decode_tgpr_5k_${t}_${enhan}_it$it \
$dir/decode_tgpr_5k_${t}_${enhan}_${lm_suffix}
done
# rescored results by high-order n-gram LM
mkdir -p $dir/log
local/chime4_calc_wers.sh $dir ${enhan}_${lm_suffix} $dir/graph_tgpr_5k \
> $dir/best_wer_${enhan}_${lm_suffix}.result
head -n 15 $dir/best_wer_${enhan}_${lm_suffix}.result
fi
# N-best rescoring using a RNNLM
if [ $stage -le 4 ]; then
# check the best lmw
if [ ! -f $dir/log/best_wer_${enhan}_${lm_suffix} ]; then
echo "error, rescoring with a high-order n-gram seems to be failed"
exit 1;
fi
lmw=`cut -f 1 -d" " $dir/log/best_wer_${enhan}_${lm_suffix} | awk -F'[_]' '{print $NF}'`
# rescore n-best list for all sets
if $eval_flag; then
tasks="dt05_simu dt05_real et05_simu et05_real"
else
tasks="dt05_simu dt05_real"
fi
for t in $tasks; do
steps/rnnlmrescore.sh --inv-acwt $lmw --N $nbest --use-phi true \
$rnnweight \
data/lang_test_${lm_suffix} \
data/lang_test_${rnnlm_suffix} \
data-fmllr-tri3b/${t}_$enhan \
$dir/decode_tgpr_5k_${t}_${enhan}_${lm_suffix} \
$dir/decode_tgpr_5k_${t}_${enhan}_${rnnlm_suffix}_w${rnnweight}_n${nbest}
done
# calc wers for RNNLM results
local/chime4_calc_wers.sh $dir ${enhan}_${rnnlm_suffix}_w${rnnweight}_n${nbest} $dir/graph_tgpr_5k \
> $dir/best_wer_${enhan}_${rnnlm_suffix}_w${rnnweight}_n${nbest}.result
head -n 15 $dir/best_wer_${enhan}_${rnnlm_suffix}_w${rnnweight}_n${nbest}.result
fi
|