update

嘉渊

2023-07-23 3aad0e15ecf53aa22e89c82f48fcf356df16df20

update

 egs/callhome/eend_ola/local/dump_feature.py

@@ -34,7 +34,7 @@
        utt2spk_file = os.path.join(self.data_dir, 'utt2spk.{}'.format(idx))
        self.utt2spk = load_utt2spk(utt2spk_file)

        wav_file = os.path.join(self.data_dir, 'wav.{}.scp'.format(idx))
        wav_file = os.path.join(self.data_dir, 'wav.scp.{}'.format(idx))
        self.wavs = load_wav_scp(wav_file)

        reco2dur_file = os.path.join(self.data_dir, 'reco2dur.{}'.format(idx))

 egs/callhome/eend_ola/run_test.sh

@@ -3,7 +3,7 @@
. ./path.sh || exit 1;

# machines configuration
CUDA_VISIBLE_DEVICES="7"
CUDA_VISIBLE_DEVICES="0"
gpu_num=$(echo $CUDA_VISIBLE_DEVICES | awk -F "," '{print NF}')
count=1

@@ -12,7 +12,7 @@
nj=64

# feature configuration
data_dir="/nfs/wangjiaming.wjm/EEND_DATA_sad30_snr10n15n20/convert_test/data"
data_dir="./data"
simu_feats_dir="/nfs/wangjiaming.wjm/EEND_ARK_DATA/dump/simu_data/data"
simu_feats_dir_chunk2000="/nfs/wangjiaming.wjm/EEND_ARK_DATA/dump/simu_data_chunk2000/data"
callhome_feats_dir_chunk2000="/nfs/wangjiaming.wjm/EEND_ARK_DATA/dump/callhome_chunk2000/data"
@@ -74,36 +74,68 @@
    simu_opts_sil_scale_array=(2 2 5 9)
    simu_opts_num_train=100000

    # for simulated data of chunk500 and chunk2000
    for dset in swb_sre_cv swb_sre_tr; do
        if [ "$dset" == "swb_sre_tr" ]; then
            n_mixtures=${simu_opts_num_train}
            dataset=train
        else
            n_mixtures=500
            dataset=dev
        fi
        simu_data_dir=${dset}_ns"$(IFS="n"; echo "${simu_opts_num_speaker_array[*]}")"_beta"$(IFS="n"; echo "${simu_opts_sil_scale_array[*]}")"_${n_mixtures}
        mkdir -p ${data_dir}/simu/data/${simu_data_dir}/.work
        split_scps=
        for n in $(seq $nj); do
            split_scps="$split_scps ${data_dir}/simu/data/${simu_data_dir}/.work/wav.$n.scp"
        done
        utils/split_scp.pl "${data_dir}/simu/data/${simu_data_dir}/wav.scp" $split_scps || exit 1
        python local/split.py ${data_dir}/simu/data/${simu_data_dir}
        # for chunk_size=500
        output_dir=${data_dir}/ark_data/dump/simu_data/$dataset
        mkdir -p $output_dir/.logs
        $dump_cmd --max-jobs-run $nj JOB=1:$nj $output_dir/.logs/dump.JOB.log \
#    # for simulated data of chunk500 and chunk2000
#    for dset in swb_sre_cv swb_sre_tr; do
#        if [ "$dset" == "swb_sre_tr" ]; then
#            n_mixtures=${simu_opts_num_train}
#            dataset=train
#        else
#            n_mixtures=500
#            dataset=dev
#        fi
#        simu_data_dir=${dset}_ns"$(IFS="n"; echo "${simu_opts_num_speaker_array[*]}")"_beta"$(IFS="n"; echo "${simu_opts_sil_scale_array[*]}")"_${n_mixtures}
#        mkdir -p ${data_dir}/simu/data/${simu_data_dir}/.work
#        split_scps=
#        for n in $(seq $nj); do
#            split_scps="$split_scps ${data_dir}/simu/data/${simu_data_dir}/.work/wav.scp.$n"
#        done
#        utils/split_scp.pl "${data_dir}/simu/data/${simu_data_dir}/wav.scp" $split_scps || exit 1
#        python local/split.py ${data_dir}/simu/data/${simu_data_dir}
#        # for chunk_size=500
#        output_dir=${data_dir}/ark_data/dump/simu_data/$dataset
#        mkdir -p $output_dir/.logs
#        $dump_cmd --max-jobs-run $nj JOB=1:$nj $output_dir/.logs/dump.JOB.log \
#        python local/dump_feature.py \
#              --data_dir ${data_dir}/simu/data/${simu_data_dir}/.work \
#              --output_dir $output_dir \
#              --index JOB
#        mkdir -p ${data_dir}/ark_data/dump/simu_data/data/$dataset
#        python local/gen_feats_scp.py \
#              --root_path ${data_dir}/ark_data/dump/simu_data/$dataset \
#              --out_path ${data_dir}/ark_data/dump/simu_data/data/$dataset \
#              --split_num $nj
#        grep "ns2" ${data_dir}/ark_data/dump/simu_data/data/$dataset/feats.scp > ${data_dir}/ark_data/dump/simu_data/data/$dataset/feats_2spkr.scp
#        # for chunk_size=2000
#        output_dir=${data_dir}/ark_data/dump/simu_data_chunk2000/$dataset
#        mkdir -p $output_dir/.logs
#        $dump_cmd --max-jobs-run $nj JOB=1:$nj $output_dir/.logs/dump.JOB.log \
#        python local/dump_feature.py \
#              --data_dir ${data_dir}/simu/data/${simu_data_dir}/.work \
#              --output_dir $output_dir \
#              --index JOB \
#              --num_frames 2000
#        mkdir -p ${data_dir}/ark_data/dump/simu_data_chunk2000/data/$dataset
#        python local/gen_feats_scp.py \
#              --root_path ${data_dir}/ark_data/dump/simu_data_chunk2000/$dataset \
#              --out_path ${data_dir}/ark_data/dump/simu_data_chunk2000/data/$dataset \
#              --split_num $nj
#        grep "ns2" ${data_dir}/ark_data/dump/simu_data_chunk2000/data/$dataset/feats.scp > ${data_dir}/ark_data/dump/simu_data_chunk2000/data/$dataset/feats_2spkr.scp
#    done

    # for callhome data
    for dset in callhome1_spkall callhome2_spkall; do
        find  $data_dir/eval/$dset  -maxdepth 1 -type f -exec cp {} {}.1 \;
        output_dir=${data_dir}/ark_data/dump/callhome/$dset
        python local/dump_feature.py \
              --data_dir ${data_dir}/simu/data/${simu_data_dir}/.work \
              --output_dir ${data_dir}/ark_data/dump/simu_data/$dataset \
              --index JOB
        mkdir -p ${data_dir}/ark_data/dump/simu_data/data/$dataset
              --data_dir $data_dir/eval/$dset \
              --output_dir $output_dir \
              --index 1 \
              --num_frames 2000
        mkdir -p ${data_dir}/ark_data/dump/callhome/data/$dset
        python local/gen_feats_scp.py \
              --root_path ${data_dir}/ark_data/dump/simu_data/$dataset \
              --out_path ${data_dir}/ark_data/dump/simu_data/data/$dataset \
              --split_num $nj
              --root_path ${data_dir}/ark_data/dump/callhome/$dset \
              --out_path ${data_dir}/ark_data/dump/callhome/data/$dset \
              --split_num 1
    done
fi