#!/usr/bin/env bash set -e set -u set -o pipefail stage=1 stop_stage=2 model="damo/speech_timestamp_prediction-v1-16k-offline" data_dir="./data/test" output_dir="./results" batch_size=1 gpu_inference=true # whether to perform gpu decoding gpuid_list="0,1" # set gpus, e.g., gpuid_list="0,1" njob=4 # the number of jobs for CPU decoding, if gpu_inference=false, use CPU decoding, please set njob checkpoint_dir= checkpoint_name="valid.cer_ctc.ave.pb" . utils/parse_options.sh || exit 1; if ${gpu_inference} == "true"; then nj=$(echo $gpuid_list | awk -F "," '{print NF}') else nj=$njob batch_size=1 gpuid_list="" for JOB in $(seq ${nj}); do gpuid_list=$gpuid_list"-1," done fi mkdir -p $output_dir/split split_scps="" split_texts="" for JOB in $(seq ${nj}); do split_scps="$split_scps $output_dir/split/wav.$JOB.scp" split_texts="$split_texts $output_dir/split/text.$JOB.scp" done perl utils/split_scp.pl ${data_dir}/wav.scp ${split_scps} perl utils/split_scp.pl ${data_dir}/text.txt ${split_texts} if [ -n "${checkpoint_dir}" ]; then python utils/prepare_checkpoint.py ${model} ${checkpoint_dir} ${checkpoint_name} model=${checkpoint_dir}/${model} fi if [ $stage -le 1 ] && [ $stop_stage -ge 1 ];then echo "Decoding ..." gpuid_list_array=(${gpuid_list//,/ }) for JOB in $(seq ${nj}); do { id=$((JOB-1)) gpuid=${gpuid_list_array[$id]} mkdir -p ${output_dir}/output.$JOB python infer.py \ --model ${model} \ --audio_in ${output_dir}/split/wav.$JOB.scp \ --text_in ${output_dir}/split/text.$JOB.scp \ --output_dir ${output_dir}/output.$JOB \ --batch_size ${batch_size} \ --gpuid ${gpuid} }& done wait mkdir -p ${output_dir}/timestamp_prediction for f in tp_sync tp_time; do if [ -f "${output_dir}/output.1/timestamp_prediction/${f}" ]; then for i in $(seq "${nj}"); do cat "${output_dir}/output.${i}/timestamp_prediction/${f}" done | sort -k1 >"${output_dir}/timestamp_prediction/${f}" fi done fi