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https://github.com/modelscope/FunASR
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@ -53,7 +53,7 @@ asr_config=conf/train_asr_transformer_12e_6d_3072_768.yaml
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model_dir="baseline_$(basename "${asr_config}" .yaml)_${lang}_${token_type}_${tag}"
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inference_config=conf/decode_asr_transformer.yaml
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inference_asr_model=valid.acc.ave_10best.pb
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inference_asr_model=valid.cer_ctc.ave_10best.pb
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# you can set gpu num for decoding here
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gpuid_list=$CUDA_VISIBLE_DEVICES # set gpus for decoding, the same as training stage by default
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@ -189,7 +189,7 @@ if [ ${stage} -le 4 ] && [ ${stop_stage} -ge 4 ]; then
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--asr_train_config "${asr_exp}"/config.yaml \
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--asr_model_file "${asr_exp}"/"${inference_asr_model}" \
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--output_dir "${_logdir}"/output.JOB \
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--mode paraformer \
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--mode asr \
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${_opts}
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for f in token token_int score text; do
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@ -5,19 +5,20 @@
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#. ./path.sh || exit 1;
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if [ $# != 2 ]; then
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echo "Usage: $0 <audio-path> <text-path>"
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echo " $0 /export/a05/xna/data/data_aishell/wav /export/a05/xna/data/data_aishell/transcript"
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if [ $# != 3 ]; then
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echo "Usage: $0 <audio-path> <text-path> <output-path>"
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echo " $0 /export/a05/xna/data/data_aishell/wav /export/a05/xna/data/data_aishell/transcript data"
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exit 1;
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fi
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aishell_audio_dir=$1
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aishell_text=$2/aishell_transcript_v0.8.txt
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output_dir=$3
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train_dir=data/local/train
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dev_dir=data/local/dev
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test_dir=data/local/test
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tmp_dir=data/local/tmp
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train_dir=$output_dir/data/local/train
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dev_dir=$output_dir/data/local/dev
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test_dir=$output_dir/data/local/test
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tmp_dir=$output_dir/data/local/tmp
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mkdir -p $train_dir
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mkdir -p $dev_dir
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@ -53,12 +54,12 @@ for dir in $train_dir $dev_dir $test_dir; do
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sort -u $dir/transcripts.txt > $dir/text
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done
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mkdir -p data/train data/dev data/test
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mkdir -p $output_dir/data/train $output_dir/data/dev $output_dir/data/test
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for f in wav.scp text; do
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cp $train_dir/$f data/train/$f || exit 1;
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cp $dev_dir/$f data/dev/$f || exit 1;
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cp $test_dir/$f data/test/$f || exit 1;
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cp $train_dir/$f $output_dir/data/train/$f || exit 1;
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cp $dev_dir/$f $output_dir/data/dev/$f || exit 1;
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cp $test_dir/$f $output_dir/data/test/$f || exit 1;
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done
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echo "$0: AISHELL data preparation succeeded"
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105
egs/aishell/paraformerbert/local/download_and_untar.sh
Executable file
105
egs/aishell/paraformerbert/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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@ -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=5
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njob=1
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train_cmd=utils/run.pl
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infer_cmd=utils/run.pl
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