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76 lines
2.2 KiB
76 lines
2.2 KiB
3 years ago
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#!/bin/bash
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set +x
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set -e
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. path.sh
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# 1. compile
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if [ ! -d ${SPEECHX_EXAMPLES} ]; then
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pushd ${SPEECHX_ROOT}
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bash build.sh
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popd
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fi
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# 2. download model
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if [ ! -d ../paddle_asr_model ]; then
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wget -c https://paddlespeech.bj.bcebos.com/s2t/paddle_asr_online/paddle_asr_model.tar.gz
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tar xzfv paddle_asr_model.tar.gz
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mv ./paddle_asr_model ../
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# produce wav scp
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echo "utt1 " $PWD/../paddle_asr_model/BAC009S0764W0290.wav > ../paddle_asr_model/wav.scp
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fi
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mkdir -p data
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if [ ! -d ./test ]; then
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wget -c https://paddlespeech.bj.bcebos.com/s2t/paddle_asr_online/aishell_test.zip
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unzip aishell_test.zip
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realpath ./test/*/*.wav > wavlist
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awk -F '/' '{ print $(NF) }' wavlist | awk -F '.' '{ print $1 }' > utt_id
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paste utt_id wavlist > aishell_test.scp
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fi
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if [ ! -d aishell_ds2_online_model ]; then
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mkdir -p aishell_ds2_online_model
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wget -P ./aishell_ds2_online_model -c https://paddlespeech.bj.bcebos.com/s2t/aishell/asr0/aishell_ds2_online_cer8.00_release.tar.gz
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tar xzfv ./aishell_ds2_online_model/aishell_ds2_online_cer8.00_release.tar.gz -C ./aishell_ds2_online_model
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fi
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# 3. make feature
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aishell_wav_scp=./aishell_test.scp
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aishell_online_model=./aishell_ds2_online_model/exp/deepspeech2_online/checkpoints
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model_dir=../paddle_asr_model
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feat_ark=./feats.ark
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feat_scp=./aishell_feat.scp
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cmvn=./cmvn.ark
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label_file=./aishell_result
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wer=./aishell_wer
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export GLOG_logtostderr=1
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# 3. gen linear feat
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linear_spectrogram_main \
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--wav_rspecifier=scp:$aishell_wav_scp \
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--feature_wspecifier=ark,scp:$feat_ark,$feat_scp \
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--cmvn_write_path=$cmvn \
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--streaming_chunk=10
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nj=10
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data=./data
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text=./test/text
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# recognizer
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./local/split_data.sh data aishell_feat.scp $nj
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utils/run.pl JOB=1:$nj $data/split${nj}/JOB/log \
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offline_decoder_sliding_chunk_main \
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--feature_rspecifier=scp:$data/split${nj}/JOB/feats.scp \
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--model_path=$aishell_online_model/avg_1.jit.pdmodel \
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--param_path=$aishell_online_model/avg_1.jit.pdiparams \
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--dict_file=$model_dir/vocab.txt \
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--lm_path=$model_dir/avg_1.jit.klm \
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--result_wspecifier=ark,t:$data/split${nj}/JOB/result
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cat $data/split${nj}/*/result > $label_file
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local/compute-wer.py --char=1 --v=1 $label_file $text > $wer
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