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105
egs/aishell/conformer/local/download_and_untar.sh
Executable file
105
egs/aishell/conformer/local/download_and_untar.sh
Executable file
@ -0,0 +1,105 @@
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#!/usr/bin/env bash
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# Copyright 2014 Johns Hopkins University (author: Daniel Povey)
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# 2017 Xingyu Na
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# Apache 2.0
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remove_archive=false
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if [ "$1" == --remove-archive ]; then
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remove_archive=true
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shift
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fi
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if [ $# -ne 3 ]; then
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echo "Usage: $0 [--remove-archive] <data-base> <url-base> <corpus-part>"
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echo "e.g.: $0 /export/a05/xna/data www.openslr.org/resources/33 data_aishell"
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echo "With --remove-archive it will remove the archive after successfully un-tarring it."
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echo "<corpus-part> can be one of: data_aishell, resource_aishell."
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fi
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data=$1
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url=$2
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part=$3
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if [ ! -d "$data" ]; then
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echo "$0: no such directory $data"
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exit 1;
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fi
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part_ok=false
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list="data_aishell resource_aishell"
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for x in $list; do
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if [ "$part" == $x ]; then part_ok=true; fi
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done
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if ! $part_ok; then
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echo "$0: expected <corpus-part> to be one of $list, but got '$part'"
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exit 1;
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fi
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if [ -z "$url" ]; then
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echo "$0: empty URL base."
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exit 1;
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fi
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if [ -f $data/$part/.complete ]; then
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echo "$0: data part $part was already successfully extracted, nothing to do."
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exit 0;
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fi
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# sizes of the archive files in bytes.
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sizes="15582913665 1246920"
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if [ -f $data/$part.tgz ]; then
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size=$(/bin/ls -l $data/$part.tgz | awk '{print $5}')
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size_ok=false
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for s in $sizes; do if [ $s == $size ]; then size_ok=true; fi; done
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if ! $size_ok; then
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echo "$0: removing existing file $data/$part.tgz because its size in bytes $size"
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echo "does not equal the size of one of the archives."
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rm $data/$part.tgz
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else
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echo "$data/$part.tgz exists and appears to be complete."
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fi
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fi
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if [ ! -f $data/$part.tgz ]; then
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if ! command -v wget >/dev/null; then
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echo "$0: wget is not installed."
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exit 1;
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fi
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full_url=$url/$part.tgz
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echo "$0: downloading data from $full_url. This may take some time, please be patient."
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cd $data || exit 1
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if ! wget --no-check-certificate $full_url; then
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echo "$0: error executing wget $full_url"
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exit 1;
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fi
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fi
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cd $data || exit 1
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if ! tar -xvzf $part.tgz; then
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echo "$0: error un-tarring archive $data/$part.tgz"
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exit 1;
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fi
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touch $data/$part/.complete
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if [ $part == "data_aishell" ]; then
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cd $data/$part/wav || exit 1
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for wav in ./*.tar.gz; do
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echo "Extracting wav from $wav"
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tar -zxf $wav && rm $wav
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done
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fi
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echo "$0: Successfully downloaded and un-tarred $data/$part.tgz"
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if $remove_archive; then
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echo "$0: removing $data/$part.tgz file since --remove-archive option was supplied."
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rm $data/$part.tgz
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fi
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exit 0;
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@ -1,53 +0,0 @@
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#!/usr/bin/env bash
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# Copyright 2018 AIShell-Foundation(Authors:Jiayu DU, Xingyu NA, Bengu WU, Hao ZHENG)
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# 2018 Beijing Shell Shell Tech. Co. Ltd. (Author: Hui BU)
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# Apache 2.0
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# transform raw AISHELL-2 data to kaldi format
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. ./path.sh || exit 1;
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tmp=
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dir=
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if [ $# != 3 ]; then
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echo "Usage: $0 <corpus-data-dir> <tmp-dir> <output-dir>"
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echo " $0 /export/AISHELL-2/iOS/train data/local/train data/train"
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exit 1;
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fi
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corpus=$1
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tmp=$2
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dir=$3
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echo "prepare_data.sh: Preparing data in $corpus"
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mkdir -p $tmp
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mkdir -p $dir
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# corpus check
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if [ ! -d $corpus ] || [ ! -f $corpus/wav.scp ] || [ ! -f $corpus/trans.txt ]; then
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echo "Error: $0 requires wav.scp and trans.txt under $corpus directory."
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exit 1;
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fi
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# validate utt-key list, IC0803W0380 is a bad utterance
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awk '{print $1}' $corpus/wav.scp | grep -v 'IC0803W0380' > $tmp/wav_utt.list
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awk '{print $1}' $corpus/trans.txt > $tmp/trans_utt.list
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utils/filter_scp.pl -f 1 $tmp/wav_utt.list $tmp/trans_utt.list > $tmp/utt.list
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# wav.scp
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awk -F'\t' -v path_prefix=$corpus '{printf("%s\t%s/%s\n",$1,path_prefix,$2)}' $corpus/wav.scp > $tmp/tmp_wav.scp
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utils/filter_scp.pl -f 1 $tmp/utt.list $tmp/tmp_wav.scp | sort -k 1 | uniq > $tmp/wav.scp
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# text
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utils/filter_scp.pl -f 1 $tmp/utt.list $corpus/trans.txt | sort -k 1 | uniq > $tmp/text
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# copy prepared resources from tmp_dir to target dir
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mkdir -p $dir
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for f in wav.scp text; do
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cp $tmp/$f $dir/$f || exit 1;
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done
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echo "local/prepare_data.sh succeeded"
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exit 0;
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@ -8,7 +8,7 @@ gpu_num=2
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count=1
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gpu_inference=true # Whether to perform gpu decoding, set false for cpu decoding
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# for gpu decoding, inference_nj=ngpu*njob; for cpu decoding, inference_nj=njob
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njob=1
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njob=5
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train_cmd=utils/run.pl
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infer_cmd=utils/run.pl
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@ -16,10 +16,9 @@ infer_cmd=utils/run.pl
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feats_dir="../DATA" #feature output dictionary
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exp_dir="."
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lang=zh
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feats_type=fbank
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token_type=char
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scp=wav.scp
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type=sound
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scp=wav.scp
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stage=3
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stop_stage=4
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@ -47,7 +46,7 @@ valid_set=dev
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test_sets="dev test"
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asr_config=conf/train_asr_conformer.yaml
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model_dir="baseline_$(basename "${asr_config}" .yaml)_${feats_type}_${lang}_${token_type}_${tag}"
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model_dir="baseline_$(basename "${asr_config}" .yaml)_${lang}_${token_type}_${tag}"
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inference_config=conf/decode_asr_transformer.yaml
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inference_asr_model=valid.acc.ave_10best.pb
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97
egs/librispeech_100h/conformer/local/download_and_untar.sh
Executable file
97
egs/librispeech_100h/conformer/local/download_and_untar.sh
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@ -0,0 +1,97 @@
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#!/usr/bin/env bash
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# Copyright 2014 Johns Hopkins University (author: Daniel Povey)
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# Apache 2.0
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remove_archive=false
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if [ "$1" == --remove-archive ]; then
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remove_archive=true
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shift
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fi
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if [ $# -ne 3 ]; then
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echo "Usage: $0 [--remove-archive] <data-base> <url-base> <corpus-part>"
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echo "e.g.: $0 /export/a15/vpanayotov/data www.openslr.org/resources/11 dev-clean"
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echo "With --remove-archive it will remove the archive after successfully un-tarring it."
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echo "<corpus-part> can be one of: dev-clean, test-clean, dev-other, test-other,"
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echo " train-clean-100, train-clean-360, train-other-500."
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exit 1
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fi
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data=$1
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url=$2
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part=$3
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if [ ! -d "$data" ]; then
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echo "$0: no such directory $data"
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exit 1
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fi
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part_ok=false
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list="dev-clean test-clean dev-other test-other train-clean-100 train-clean-360 train-other-500"
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for x in $list; do
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if [ "$part" == $x ]; then part_ok=true; fi
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done
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if ! $part_ok; then
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echo "$0: expected <corpus-part> to be one of $list, but got '$part'"
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exit 1
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fi
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if [ -z "$url" ]; then
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echo "$0: empty URL base."
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exit 1
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fi
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if [ -f $data/LibriSpeech/$part/.complete ]; then
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echo "$0: data part $part was already successfully extracted, nothing to do."
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exit 0
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fi
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# sizes of the archive files in bytes. This is some older versions.
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sizes_old="371012589 347390293 379743611 361838298 6420417880 23082659865 30626749128"
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# sizes_new is the archive file sizes of the final release. Some of these sizes are of
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# things we probably won't download.
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sizes_new="337926286 314305928 695964615 297279345 87960560420 33373768 346663984 328757843 6387309499 23049477885 30593501606"
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if [ -f $data/$part.tar.gz ]; then
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size=$(/bin/ls -l $data/$part.tar.gz | awk '{print $5}')
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size_ok=false
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for s in $sizes_old $sizes_new; do if [ $s == $size ]; then size_ok=true; fi; done
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if ! $size_ok; then
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echo "$0: removing existing file $data/$part.tar.gz because its size in bytes $size"
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echo "does not equal the size of one of the archives."
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rm $data/$part.tar.gz
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else
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echo "$data/$part.tar.gz exists and appears to be complete."
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fi
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fi
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if [ ! -f $data/$part.tar.gz ]; then
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if ! which wget >/dev/null; then
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echo "$0: wget is not installed."
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exit 1
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fi
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full_url=$url/$part.tar.gz
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echo "$0: downloading data from $full_url. This may take some time, please be patient."
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if ! wget -P $data --no-check-certificate $full_url; then
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echo "$0: error executing wget $full_url"
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exit 1
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fi
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fi
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if ! tar -C $data -xvzf $data/$part.tar.gz; then
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echo "$0: error un-tarring archive $data/$part.tar.gz"
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exit 1
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fi
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touch $data/LibriSpeech/$part/.complete
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echo "$0: Successfully downloaded and un-tarred $data/$part.tar.gz"
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if $remove_archive; then
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echo "$0: removing $data/$part.tar.gz file since --remove-archive option was supplied."
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rm $data/$part.tar.gz
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fi
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@ -3,8 +3,8 @@
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. ./path.sh || exit 1;
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# machines configuration
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CUDA_VISIBLE_DEVICES="0,1,2,3,4,5,6,7"
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gpu_num=8
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CUDA_VISIBLE_DEVICES="0,1"
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gpu_num=2
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count=1
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gpu_inference=true # Whether to perform gpu decoding, set false for cpu decoding
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# for gpu decoding, inference_nj=ngpu*njob; for cpu decoding, inference_nj=njob
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@ -16,30 +16,26 @@ infer_cmd=utils/run.pl
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feats_dir="../DATA" #feature output dictionary
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exp_dir="."
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lang=en
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dumpdir=dump/fbank
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feats_type=fbank
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token_type=bpe
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dataset_type=large
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scp=feats.scp
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type=kaldi_ark
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stage=3
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stop_stage=4
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type=sound
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scp=wav.scp
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stage=1
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stop_stage=1
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# feature configuration
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feats_dim=80
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sample_frequency=16000
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nj=100
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speed_perturb="0.9,1.0,1.1"
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nj=64
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# data
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data_librispeech=
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raw_data=
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data_url=www.openslr.org/resources/12
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# bpe model
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nbpe=5000
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bpemode=unigram
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# exp tag
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tag=""
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tag="exp1"
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. utils/parse_options.sh || exit 1;
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@ -54,8 +50,7 @@ valid_set=dev
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test_sets="test_clean test_other dev_clean dev_other"
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asr_config=conf/train_asr_conformer.yaml
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#asr_config=conf/train_asr_conformer_uttnorm.yaml
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model_dir="baseline_$(basename "${asr_config}" .yaml)_${feats_type}_${lang}_${token_type}_${tag}"
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model_dir="baseline_$(basename "${asr_config}" .yaml)_${lang}_${token_type}_${tag}"
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inference_config=conf/decode_asr_transformer.yaml
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#inference_config=conf/decode_asr_transformer_beam60_ctc0.3.yaml
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@ -73,6 +68,14 @@ else
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_ngpu=0
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fi
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if [ ${stage} -le -1 ] && [ ${stop_stage} -ge -1 ]; then
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echo "stage -1: Data Download"
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for part in dev-clean test-clean dev-other test-other train-clean-100; do
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local/download_and_untar.sh ${raw_data} ${data_url} ${part}
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done
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fi
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if [ ${stage} -le 0 ] && [ ${stop_stage} -ge 0 ]; then
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echo "stage 0: Data preparation"
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# Data preparation
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