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58 lines
1.4 KiB
58 lines
1.4 KiB
#!/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 ${SPEECHX_ROOT}
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bash build.sh
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popd
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fi
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# input
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mkdir -p data
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data=$PWD/data
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ckpt_dir=$data/model
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model_dir=$ckpt_dir/exp/deepspeech2_online/checkpoints/
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vocb_dir=$ckpt_dir/data/lang_char/
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if [ ! -f $ckpt_dir/data/mean_std.json ]; then
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mkdir -p $ckpt_dir
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pushd $ckpt_dir
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wget -c https://paddlespeech.bj.bcebos.com/s2t/aishell/asr0/asr0_deepspeech2_online_aishell_ckpt_0.2.0.model.tar.gz
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tar xzfv asr0_deepspeech2_online_aishell_ckpt_0.2.0.model.tar.gz
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popd
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fi
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export GLOG_logtostderr=1
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# 3. gen cmvn
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cmvn=$data/cmvn.ark
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cmvn-json2kaldi --json_file=$ckpt_dir/data/mean_std.json --cmvn_write_path=$cmvn
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wfst=$data/wfst/
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mkdir -p $wfst
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if [ ! -f $wfst/aishell_graph.zip ]; then
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pushd $wfst
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wget -c https://paddlespeech.bj.bcebos.com/s2t/paddle_asr_online/aishell_graph.zip
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unzip aishell_graph.zip
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mv aishell_graph/* $wfst
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popd
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fi
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# 5. test websocket server
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websocket_server_main \
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--cmvn_file=$cmvn \
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--model_path=$model_dir/avg_1.jit.pdmodel \
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--streaming_chunk=0.1 \
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--convert2PCM32=true \
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--param_path=$model_dir/avg_1.jit.pdiparams \
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--word_symbol_table=$data/wfst/words.txt \
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--model_output_names=softmax_0.tmp_0,tmp_5,concat_0.tmp_0,concat_1.tmp_0 \
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--graph_path=$data/wfst/TLG.fst --max_active=7500 \
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--acoustic_scale=1.2
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