#!/bin/bash source path.sh set -e gpus=0,1,2,3 stage=0 stop_stage=50 conf_path=conf/conformer.yaml ips= #xx.xx.xx.xx,xx.xx.xx.xx decode_conf_path=conf/tuning/decode.yaml avg_num=30 audio_file=data/demo_01_03.wav source ${MAIN_ROOT}/utils/parse_options.sh || exit 1; avg_ckpt=avg_${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 # test ckpt avg_n CUDA_VISIBLE_DEVICES=0 ./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 # ctc alignment of test data CUDA_VISIBLE_DEVICES=0 ./local/align.sh ${conf_path} ${decode_conf_path} exp/${ckpt}/checkpoints/${avg_ckpt} || exit -1 fi # Optionally, you can add LM and test it with runtime. if [ ${stage} -le 5 ] && [ ${stop_stage} -ge 5 ]; then # test a single .wav file CUDA_VISIBLE_DEVICES=0 ./local/test_wav.sh ${conf_path} ${decode_conf_path} exp/${ckpt}/checkpoints/${avg_ckpt} ${audio_file} || exit -1 fi # Not supported at now!!! if [ ${stage} -le 51 ] && [ ${stop_stage} -ge 51 ]; then # export ckpt avg_n CUDA_VISIBLE_DEVICES=0 ./local/export.sh ${conf_path} exp/${ckpt}/checkpoints/${avg_ckpt} exp/${ckpt}/checkpoints/${avg_ckpt}.jit fi # Need further installation! Read the install.md to complete further installation if [ ${stage} -le 101 ] && [ ${stop_stage} -ge 101 ]; then echo "warning: deps on kaldi and srilm, please make sure installed." # train lm and build TLG ./local/tlg.sh --corpus aishell --lmtype srilm fi