#!/usr/bin/env bash
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set -e
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set -u
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set -o pipefail
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ori_data=
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data_dir=
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exp_dir=
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model_name=speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch
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model_revision="v1.0.4" # please do not modify the model revision
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inference_nj=32
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gpuid_list="0,1" # set gpus, e.g., gpuid_list="0,1"
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ngpu=$(echo $gpuid_list | awk -F "," '{print NF}')
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njob=4 # the number of jobs for each gpu
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gpu_inference=true # Whether to perform gpu decoding, set false for cpu decoding
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if ${gpu_inference}; then
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inference_nj=$[${ngpu}*${njob}]
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else
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inference_nj=$njob
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fi
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# LM configs
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use_lm=false
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beam_size=1
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lm_weight=0.0
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test_sets="dev test_meeting test_net"
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. utils/parse_options.sh
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for tset_name in ${test_sets}; do
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test_dir=${data_dir}/wenetspeech/${tset_name}
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mkdir -p ${test_dir}
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find ${ori_data}/${tset_name} -iname "*.wav" > ${test_dir}/wav.flist
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sed -e 's/\.wav//' ${test_dir}/wav.flist | awk -F '/' '{print $NF}' > ${test_dir}/utt.list
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paste -d' ' ${test_dir}/utt.list ${test_dir}/wav.flist > ${test_dir}/wav.scp
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cp ${ori_data}/${tset_name}/trans.txt ${test_dir}/text
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sed -i "s/\t/ /g" ${test_dir}/text
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done
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mkdir -p ${exp_dir}/wenetspeech
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modelscope_utils/modelscope_infer.sh \
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--data_dir ${data_dir}/wenetspeech \
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--exp_dir ${exp_dir}/wenetspeech \
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--test_sets "${test_sets}" \
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--model_name ${model_name} \
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--model_revision ${model_revision} \
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--inference_nj ${inference_nj} \
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--gpuid_list ${gpuid_list} \
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--njob ${njob} \
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--gpu_inference ${gpu_inference} \
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--use_lm ${use_lm} \
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--beam_size ${beam_size} \
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--lm_weight ${lm_weight}
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