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PaddleSpeech/examples/librispeech/asr3/run.sh

48 lines
1.3 KiB

#!/bin/bash
set -e
. ./path.sh || exit 1;
. ./cmd.sh || exit 1;
gpus=0
stage=0
stop_stage=0
conf_path=conf/wav2vec2ASR.yaml
ips= #xx.xx.xx.xx,xx.xx.xx.xx
decode_conf_path=conf/tuning/decode.yaml
avg_num=1
dict_path=data/lang_char/vocab.txt
. ${MAIN_ROOT}/utils/parse_options.sh || exit 1;
audio_file=data/demo_002_en.wav
avg_ckpt=avg_${avg_num}
ckpt=$(basename ${conf_path} | awk -F'.' '{print $1}')
echo "checkpoint name ${ckpt}"
if [ ${stage} -le 0 ] && [ ${stop_stage} -ge 0 ]; then
# prepare data
bash ./local/data.sh || exit -1
fi
if [ ${stage} -le 1 ] && [ ${stop_stage} -ge 1 ]; then
# train model, all `ckpt` under `exp` dir
CUDA_VISIBLE_DEVICES=${gpus} ./local/train.sh ${conf_path} ${ckpt} ${ips}
fi
if [ ${stage} -le 2 ] && [ ${stop_stage} -ge 2 ]; then
# avg n best model
avg.sh best exp/${ckpt}/checkpoints ${avg_num}
fi
if [ ${stage} -le 3 ] && [ ${stop_stage} -ge 3 ]; then
# greedy search decoder
CUDA_VISIBLE_DEVICES=${gpus} ./local/test.sh ${conf_path} ${decode_conf_path} exp/${ckpt}/checkpoints/${avg_ckpt} || exit -1
fi
if [ ${stage} -le 4 ] && [ ${stop_stage} -ge 4 ]; then
# test a single .wav file
CUDA_VISIBLE_DEVICES=${gpus} ./local/test_wav.sh ${conf_path} ${decode_conf_path} exp/${ckpt}/checkpoints/${avg_ckpt} ${audio_file} || exit -1
fi