| set -x | |
| meta_lst=$1 | |
| output_dir=$2 | |
| dataset_lst=$3 | |
| checkpoint_path=wavlm_large_finetune.pth | |
| wav_wav_text=$output_dir/wav_res_ref_text | |
| score_file=$output_dir/wav_res_ref_text.wer | |
| python3 get_wav_res_ref_text.py $meta_lst $output_dir $dataset_lst $wav_wav_text | |
| workdir=$(cd $(dirname $0); pwd) | |
| cd $workdir/thirdparty/UniSpeech/downstreams/speaker_verification/ | |
| # 单进程运行 | |
| temp_result_file=$output_dir/temp_sim_result.out | |
| python3 verification_pair_list_v2.py $wav_wav_text \ | |
| --model_name wavlm_large \ | |
| --checkpoint $checkpoint_path \ | |
| --scores $temp_result_file \ | |
| --wav1_start_sr 0 \ | |
| --wav2_start_sr 0 \ | |
| --wav1_end_sr -1 \ | |
| --wav2_end_sr -1 \ | |
| --device cuda:0 | |
| # 过滤掉 "avg score" 行并计算平均分数 | |
| temp_clean_file=$output_dir/temp_sim_clean.out | |
| grep -v "avg score" $temp_result_file > $temp_clean_file | |
| python3 average.py $temp_clean_file $score_file | |
| # 清理临时文件 | |
| rm $wav_wav_text | |
| rm $temp_result_file | |
| rm $temp_clean_file | |