update

嘉渊

2023-07-20 7fb605cc8831227c3a66d2c9da93dffa8049a5c1

update

 egs/callhome/eend_ola/run.sh

@@ -94,7 +94,6 @@
    done
fi


# Training on simulated two-speaker data
world_size=$gpu_num
simu_2spkr_ave_id=avg${simu_average_2spkr_start}-${simu_average_2spkr_end}

 egs/callhome/eend_ola/run_test.sh

@@ -8,6 +8,11 @@
count=1

# general configuration
dump_cmd=utils/run.pl
nj=64

# feature configuration
data_dir="/nfs/wangjiaming.wjm/EEND_DATA_sad30_snr10n15n20/convert_chunk2000/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"
@@ -27,8 +32,8 @@

exp_dir="."
input_size=345
stage=5
stop_stage=5
stage=0
stop_stage=0

# exp tag
tag="exp1"
@@ -62,13 +67,32 @@
    local/run_prepare_shared_eda.sh
fi

## Prepare data for training and inference
#if [ ${stage} -le 0 ] && [ ${stop_stage} -ge 0 ]; then
#    echo "stage 0: Prepare data for training and inference"
#    echo "The detail can be found in https://github.com/hitachi-speech/EEND"
#    . ./local/
#fi
#
# Prepare data for training and inference
if [ ${stage} -le 0 ] && [ ${stop_stage} -ge 0 ]; then
    echo "stage 0: Prepare data for training and inference"
    simu_opts_num_speaker_array=(1 2 3 4)
    simu_opts_sil_scale_array=(2 2 5 9)
    simu_opts_num_speaker=${simu_opts_num_speaker_array[i]}
    simu_opts_sil_scale=${simu_opts_sil_scale_array[i]}
    simu_opts_num_train=100000

    # for simulated data of chunk500
    for dset in swb_sre_tr swb_sre_cv; do
        if [ "$dset" == "swb_sre_tr" ]; then
            n_mixtures=${simu_opts_num_train}
        else
            n_mixtures=500
        fi
        simu_data_dir=${dset}_ns${simu_opts_num_speaker}_beta${simu_opts_sil_scale}_${n_mixtures}
        mkdir ${data_dir}/simu/data/${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}
    done
fi

# Training on simulated two-speaker data
world_size=$gpu_num