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[egs] Add mini-librispeech example scripts [intended as a sanity-chec…
…ker/tutorial setup] (#1566)
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#!/bin/bash | ||
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for x in exp/*/decode*; do [ -d $x ] && [[ $x =~ "$1" ]] && grep WER $x/wer_* | utils/best_wer.sh; done | ||
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for x in exp/chain/*/decode*; do [ -d $x ] && [[ $x =~ "$1" ]] && grep WER $x/wer_* | utils/best_wer.sh; done | ||
exit 0 | ||
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# Results on on dev_clean_2 | ||
%WER 49.18 [ 9903 / 20138, 439 ins, 2332 del, 7132 sub ] exp/mono/decode_nosp_tgsmall_dev_clean_2/wer_8_0.0 | ||
%WER 20.42 [ 4113 / 20138, 469 ins, 545 del, 3099 sub ] exp/tri1/decode_nosp_tglarge_dev_clean_2/wer_14_0.0 | ||
%WER 24.56 [ 4945 / 20138, 447 ins, 792 del, 3706 sub ] exp/tri1/decode_nosp_tgmed_dev_clean_2/wer_14_0.0 | ||
%WER 27.37 [ 5512 / 20138, 425 ins, 969 del, 4118 sub ] exp/tri1/decode_nosp_tgsmall_dev_clean_2/wer_14_0.0 | ||
%WER 18.59 [ 3743 / 20138, 435 ins, 517 del, 2791 sub ] exp/tri2b/decode_nosp_tglarge_dev_clean_2/wer_15_0.0 | ||
%WER 22.06 [ 4443 / 20138, 400 ins, 748 del, 3295 sub ] exp/tri2b/decode_nosp_tgmed_dev_clean_2/wer_15_0.0 | ||
%WER 24.32 [ 4898 / 20138, 413 ins, 899 del, 3586 sub ] exp/tri2b/decode_nosp_tgsmall_dev_clean_2/wer_15_0.0 | ||
%WER 13.45 [ 2708 / 20138, 358 ins, 330 del, 2020 sub ] exp/tri3b/decode_nosp_tglarge_dev_clean_2/wer_17_0.0 | ||
%WER 16.25 [ 3273 / 20138, 332 ins, 485 del, 2456 sub ] exp/tri3b/decode_nosp_tgmed_dev_clean_2/wer_16_0.0 | ||
%WER 18.10 [ 3645 / 20138, 332 ins, 603 del, 2710 sub ] exp/tri3b/decode_nosp_tgsmall_dev_clean_2/wer_16_0.0 | ||
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%WER 18.58 [ 3742 / 20138, 366 ins, 763 del, 2613 sub ] exp/chain/tdnn1a_sp/decode_tgsmall_dev_clean_2/wer_10_0.0 | ||
%WER 13.35 [ 2689 / 20138, 318 ins, 491 del, 1880 sub ] exp/chain/tdnn1a_sp/decode_tglarge_dev_clean_2/wer_9_0.5 |
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# you can change cmd.sh depending on what type of queue you are using. | ||
# If you have no queueing system and want to run on a local machine, you | ||
# can change all instances 'queue.pl' to run.pl (but be careful and run | ||
# commands one by one: most recipes will exhaust the memory on your | ||
# machine). queue.pl works with GridEngine (qsub). slurm.pl works | ||
# with slurm. Different queues are configured differently, with different | ||
# queue names and different ways of specifying things like memory; | ||
# to account for these differences you can create and edit the file | ||
# conf/queue.conf to match your queue's configuration. Search for | ||
# conf/queue.conf in http://kaldi-asr.org/doc/queue.html for more information, | ||
# or search for the string 'default_config' in utils/queue.pl or utils/slurm.pl. | ||
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export train_cmd="queue.pl --mem 2G" | ||
export decode_cmd="queue.pl --mem 4G" | ||
export mkgraph_cmd="queue.pl --mem 8G" |
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--use-energy=false # only non-default option. |
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# config for high-resolution MFCC features, intended for neural network training | ||
# Note: we keep all cepstra, so it has the same info as filterbank features, | ||
# but MFCC is more easily compressible (because less correlated) which is why | ||
# we prefer this method. | ||
--use-energy=false # use average of log energy, not energy. | ||
--num-mel-bins=40 # similar to Google's setup. | ||
--num-ceps=40 # there is no dimensionality reduction. | ||
--low-freq=20 # low cutoff frequency for mel bins... this is high-bandwidth data, so | ||
# there might be some information at the low end. | ||
--high-freq=-400 # high cutoff frequently, relative to Nyquist of 8000 (=7600) |
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# configuration file for apply-cmvn-online, used in the script ../local/run_online_decoding.sh |
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#!/bin/bash | ||
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# this script is used for comparing decoding results between systems. | ||
# e.g. local/chain/compare_wer.sh exp/chain/tdnn_{c,d}_sp | ||
# For use with discriminatively trained systems you specify the epochs after a colon: | ||
# for instance, | ||
# local/chain/compare_wer.sh exp/chain/tdnn_c_sp exp/chain/tdnn_c_sp_smbr:{1,2,3} | ||
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if [ $# == 0 ]; then | ||
echo "Usage: $0: [--looped] [--online] <dir1> [<dir2> ... ]" | ||
echo "e.g.: $0 exp/chain/tdnn_{b,c}_sp" | ||
echo "or (with epoch numbers for discriminative training):" | ||
echo "$0 exp/chain/tdnn_b_sp_disc:{1,2,3}" | ||
exit 1 | ||
fi | ||
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echo "# $0 $*" | ||
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include_looped=false | ||
if [ "$1" == "--looped" ]; then | ||
include_looped=true | ||
shift | ||
fi | ||
include_online=false | ||
if [ "$1" == "--online" ]; then | ||
include_online=true | ||
shift | ||
fi | ||
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used_epochs=false | ||
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# this function set_names is used to separate the epoch-related parts of the name | ||
# [for discriminative training] and the regular parts of the name. | ||
# If called with a colon-free directory name, like: | ||
# set_names exp/chain/tdnn_lstm1e_sp_bi_smbr | ||
# it will set dir=exp/chain/tdnn_lstm1e_sp_bi_smbr and epoch_infix="" | ||
# If called with something like: | ||
# set_names exp/chain/tdnn_d_sp_smbr:3 | ||
# it will set dir=exp/chain/tdnn_d_sp_smbr and epoch_infix="_epoch3" | ||
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set_names() { | ||
if [ $# != 1 ]; then | ||
echo "compare_wer_general.sh: internal error" | ||
exit 1 # exit the program | ||
fi | ||
dirname=$(echo $1 | cut -d: -f1) | ||
epoch=$(echo $1 | cut -s -d: -f2) | ||
if [ -z $epoch ]; then | ||
epoch_infix="" | ||
else | ||
used_epochs=true | ||
epoch_infix=_epoch${epoch} | ||
fi | ||
} | ||
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echo -n "# System " | ||
for x in $*; do printf "% 10s" " $(basename $x)"; done | ||
echo | ||
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strings=( | ||
"#WER dev_clean_2 (tgsmall) " | ||
"#WER dev_clean_2 (tglarge) ") | ||
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for n in 0 1; do | ||
echo -n "${strings[$n]}" | ||
for x in $*; do | ||
set_names $x # sets $dirname and $epoch_infix | ||
decode_names=(tgsmall_dev_clean_2 tglarge_dev_clean_2) | ||
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wer=$(cat $dirname/decode_${decode_names[$n]}/wer_* | utils/best_wer.sh | awk '{print $2}') | ||
printf "% 10s" $wer | ||
done | ||
echo | ||
if $include_looped; then | ||
echo -n "# [looped:] " | ||
for x in $*; do | ||
set_names $x # sets $dirname and $epoch_infix | ||
wer=$(cat $dirname/decode_looped_${decode_names[$n]}/wer_* | utils/best_wer.sh | awk '{print $2}') | ||
printf "% 10s" $wer | ||
done | ||
echo | ||
fi | ||
if $include_online; then | ||
echo -n "# [online:] " | ||
for x in $*; do | ||
set_names $x # sets $dirname and $epoch_infix | ||
wer=$(cat ${dirname}_online/decode_${decode_names[$n]}/wer_* | utils/best_wer.sh | awk '{print $2}') | ||
printf "% 10s" $wer | ||
done | ||
echo | ||
fi | ||
done | ||
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if $used_epochs; then | ||
exit 0; # the diagnostics aren't comparable between regular and discriminatively trained systems. | ||
fi | ||
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echo -n "# Final train prob " | ||
for x in $*; do | ||
prob=$(grep Overall $x/log/compute_prob_train.final.log | grep -v xent | awk '{printf("%.4f", $8)}') | ||
printf "% 10s" $prob | ||
done | ||
echo | ||
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echo -n "# Final valid prob " | ||
for x in $*; do | ||
prob=$(grep Overall $x/log/compute_prob_valid.final.log | grep -v xent | awk '{printf("%.4f", $8)}') | ||
printf "% 10s" $prob | ||
done | ||
echo | ||
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echo -n "# Final train prob (xent)" | ||
for x in $*; do | ||
prob=$(grep Overall $x/log/compute_prob_train.final.log | grep -w xent | awk '{printf("%.4f", $8)}') | ||
printf "% 10s" $prob | ||
done | ||
echo | ||
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echo -n "# Final valid prob (xent)" | ||
for x in $*; do | ||
prob=$(grep Overall $x/log/compute_prob_valid.final.log | grep -w xent | awk '{printf("%.4f", $8)}') | ||
printf "% 10s" $prob | ||
done | ||
echo |
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tuning/run_tdnn_1a.sh |
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