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PaddleSpeech/examples/aishell/asr1/local/test.sh

119 lines
3.5 KiB

#!/bin/bash
set -e
stage=0
stop_stage=100
source utils/parse_options.sh || exit 1;
ngpu=$(echo $CUDA_VISIBLE_DEVICES | awk -F "," '{print NF}')
echo "using $ngpu gpus..."
if [ $# != 3 ];then
echo "usage: ${0} config_path decode_config_path ckpt_path_prefix"
exit -1
fi
config_path=$1
decode_config_path=$2
ckpt_prefix=$3
chunk_mode=false
if [[ ${config_path} =~ ^.*chunk_.*yaml$ ]];then
chunk_mode=true
fi
# download language model
#bash local/download_lm_ch.sh
#if [ $? -ne 0 ]; then
# exit 1
#fi
if [ ${stage} -le 0 ] && [ ${stop_stage} -ge 0 ]; then
# format the reference test file
python utils/format_rsl.py \
--origin_ref data/manifest.test.raw \
--trans_ref data/manifest.test.text
for type in attention ctc_greedy_search; do
echo "decoding ${type}"
if [ ${chunk_mode} == true ];then
# stream decoding only support batchsize=1
batch_size=1
else
batch_size=64
fi
output_dir=${ckpt_prefix}
mkdir -p ${output_dir}
python3 -u ${BIN_DIR}/test.py \
--ngpu ${ngpu} \
--config ${config_path} \
--decode_cfg ${decode_config_path} \
--result_file ${output_dir}/${type}.rsl \
--checkpoint_path ${ckpt_prefix} \
--opts decode.decoding_method ${type} \
--opts decode.decode_batch_size ${batch_size}
if [ $? -ne 0 ]; then
echo "Failed in evaluation!"
exit 1
fi
# format the hyp file
python utils/format_rsl.py \
--origin_hyp ${output_dir}/${type}.rsl \
--trans_hyp ${output_dir}/${type}.rsl.text
python utils/compute-wer.py --char=1 --v=1 \
data/manifest.test.text ${output_dir}/${type}.rsl.text > ${output_dir}/${type}.error
done
for type in ctc_prefix_beam_search attention_rescoring; do
echo "decoding ${type}"
batch_size=1
output_dir=${ckpt_prefix}
mkdir -p ${output_dir}
python3 -u ${BIN_DIR}/test.py \
--ngpu ${ngpu} \
--config ${config_path} \
--decode_cfg ${decode_config_path} \
--result_file ${output_dir}/${type}.rsl \
--checkpoint_path ${ckpt_prefix} \
--opts decode.decoding_method ${type} \
--opts decode.decode_batch_size ${batch_size}
if [ $? -ne 0 ]; then
echo "Failed in evaluation!"
exit 1
fi
python utils/format_rsl.py \
--origin_hyp ${output_dir}/${type}.rsl \
--trans_hyp ${output_dir}/${type}.rsl.text
python utils/compute-wer.py --char=1 --v=1 \
data/manifest.test.text ${output_dir}/${type}.rsl.text > ${output_dir}/${type}.error
done
fi
if [ ${stage} -le 101 ] && [ ${stop_stage} -ge 101 ]; then
echo "using sclite to compute cer..."
# format the reference test file for sclite
python utils/format_rsl.py \
--origin_ref data/manifest.test.raw \
--trans_ref_sclite data/manifest.test.text.sclite
output_dir=${ckpt_prefix}
for type in attention ctc_greedy_search ctc_prefix_beam_search attention_rescoring; do
python utils/format_rsl.py \
--origin_hyp ${output_dir}/${type}.rsl \
--trans_hyp_sclite ${output_dir}/${type}.rsl.text.sclite
mkdir -p ${output_dir}/${type}_sclite
sclite -i wsj -r data/manifest.test.text.sclite -h ${output_dir}/${type}.rsl.text.sclite -e utf-8 -o all -O ${output_dir}/${type}_sclite -c NOASCII
done
fi
exit 0