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PaddleSpeech/examples/ami/sd0/local/process.sh

50 lines
1.3 KiB

#!/bin/bash
stage=0
set=L
. ${MAIN_ROOT}/utils/parse_options.sh || exit 1;
set -o pipefail
data_folder=$1
manual_annot_folder=$2
save_folder=$3
pretrained_model_dir=$4
conf_path=$5
device=$6
ref_rttm_dir=${save_folder}/ref_rttms
meta_data_dir=${save_folder}/metadata
if [ ${stage} -le 0 ]; then
echo "AMI Data preparation"
python local/ami_prepare.py --data_folder ${data_folder} \
--manual_annot_folder ${manual_annot_folder} \
--save_folder ${save_folder} --ref_rttm_dir ${ref_rttm_dir} \
--meta_data_dir ${meta_data_dir}
if [ $? -ne 0 ]; then
echo "Prepare AMI failed. Please check log message."
exit 1
fi
echo "AMI data preparation done."
fi
if [ ${stage} -le 1 ]; then
# extra embddings for dev and eval dataset
for name in dev eval; do
python local/compute_embdding.py --config ${conf_path} \
--data-dir ${save_folder} \
--device ${device} \
--dataset ${name} \
--load-checkpoint ${pretrained_model_dir}
done
fi
if [ ${stage} -le 2 ]; then
# tune hyperparams on dev set
# perform final diarization on 'dev' and 'eval' with best hyperparams
python local/experiment.py --config ${conf_path} \
--data-dir ${save_folder}
fi