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https://github.com/modelscope/FunASR
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update
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嘉渊
parent
c8680dcb7b
commit
3aad0e15ec
@ -34,7 +34,7 @@ class KaldiData:
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utt2spk_file = os.path.join(self.data_dir, 'utt2spk.{}'.format(idx))
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self.utt2spk = load_utt2spk(utt2spk_file)
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wav_file = os.path.join(self.data_dir, 'wav.{}.scp'.format(idx))
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wav_file = os.path.join(self.data_dir, 'wav.scp.{}'.format(idx))
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self.wavs = load_wav_scp(wav_file)
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reco2dur_file = os.path.join(self.data_dir, 'reco2dur.{}'.format(idx))
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@ -3,7 +3,7 @@
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. ./path.sh || exit 1;
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# machines configuration
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CUDA_VISIBLE_DEVICES="7"
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CUDA_VISIBLE_DEVICES="0"
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gpu_num=$(echo $CUDA_VISIBLE_DEVICES | awk -F "," '{print NF}')
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count=1
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@ -12,7 +12,7 @@ dump_cmd=utils/run.pl
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nj=64
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# feature configuration
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data_dir="/nfs/wangjiaming.wjm/EEND_DATA_sad30_snr10n15n20/convert_test/data"
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data_dir="./data"
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simu_feats_dir="/nfs/wangjiaming.wjm/EEND_ARK_DATA/dump/simu_data/data"
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simu_feats_dir_chunk2000="/nfs/wangjiaming.wjm/EEND_ARK_DATA/dump/simu_data_chunk2000/data"
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callhome_feats_dir_chunk2000="/nfs/wangjiaming.wjm/EEND_ARK_DATA/dump/callhome_chunk2000/data"
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@ -74,36 +74,68 @@ if [ ${stage} -le 0 ] && [ ${stop_stage} -ge 0 ]; then
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simu_opts_sil_scale_array=(2 2 5 9)
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simu_opts_num_train=100000
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# for simulated data of chunk500 and chunk2000
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for dset in swb_sre_cv swb_sre_tr; do
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if [ "$dset" == "swb_sre_tr" ]; then
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n_mixtures=${simu_opts_num_train}
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dataset=train
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else
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n_mixtures=500
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dataset=dev
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fi
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simu_data_dir=${dset}_ns"$(IFS="n"; echo "${simu_opts_num_speaker_array[*]}")"_beta"$(IFS="n"; echo "${simu_opts_sil_scale_array[*]}")"_${n_mixtures}
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mkdir -p ${data_dir}/simu/data/${simu_data_dir}/.work
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split_scps=
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for n in $(seq $nj); do
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split_scps="$split_scps ${data_dir}/simu/data/${simu_data_dir}/.work/wav.$n.scp"
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done
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utils/split_scp.pl "${data_dir}/simu/data/${simu_data_dir}/wav.scp" $split_scps || exit 1
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python local/split.py ${data_dir}/simu/data/${simu_data_dir}
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# for chunk_size=500
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output_dir=${data_dir}/ark_data/dump/simu_data/$dataset
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mkdir -p $output_dir/.logs
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$dump_cmd --max-jobs-run $nj JOB=1:$nj $output_dir/.logs/dump.JOB.log \
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# # for simulated data of chunk500 and chunk2000
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# for dset in swb_sre_cv swb_sre_tr; do
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# if [ "$dset" == "swb_sre_tr" ]; then
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# n_mixtures=${simu_opts_num_train}
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# dataset=train
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# else
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# n_mixtures=500
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# dataset=dev
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# fi
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# simu_data_dir=${dset}_ns"$(IFS="n"; echo "${simu_opts_num_speaker_array[*]}")"_beta"$(IFS="n"; echo "${simu_opts_sil_scale_array[*]}")"_${n_mixtures}
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# mkdir -p ${data_dir}/simu/data/${simu_data_dir}/.work
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# split_scps=
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# for n in $(seq $nj); do
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# split_scps="$split_scps ${data_dir}/simu/data/${simu_data_dir}/.work/wav.scp.$n"
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# done
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# utils/split_scp.pl "${data_dir}/simu/data/${simu_data_dir}/wav.scp" $split_scps || exit 1
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# python local/split.py ${data_dir}/simu/data/${simu_data_dir}
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# # for chunk_size=500
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# output_dir=${data_dir}/ark_data/dump/simu_data/$dataset
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# mkdir -p $output_dir/.logs
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# $dump_cmd --max-jobs-run $nj JOB=1:$nj $output_dir/.logs/dump.JOB.log \
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# python local/dump_feature.py \
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# --data_dir ${data_dir}/simu/data/${simu_data_dir}/.work \
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# --output_dir $output_dir \
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# --index JOB
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# mkdir -p ${data_dir}/ark_data/dump/simu_data/data/$dataset
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# python local/gen_feats_scp.py \
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# --root_path ${data_dir}/ark_data/dump/simu_data/$dataset \
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# --out_path ${data_dir}/ark_data/dump/simu_data/data/$dataset \
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# --split_num $nj
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# 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
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# # for chunk_size=2000
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# output_dir=${data_dir}/ark_data/dump/simu_data_chunk2000/$dataset
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# mkdir -p $output_dir/.logs
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# $dump_cmd --max-jobs-run $nj JOB=1:$nj $output_dir/.logs/dump.JOB.log \
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# python local/dump_feature.py \
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# --data_dir ${data_dir}/simu/data/${simu_data_dir}/.work \
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# --output_dir $output_dir \
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# --index JOB \
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# --num_frames 2000
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# mkdir -p ${data_dir}/ark_data/dump/simu_data_chunk2000/data/$dataset
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# python local/gen_feats_scp.py \
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# --root_path ${data_dir}/ark_data/dump/simu_data_chunk2000/$dataset \
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# --out_path ${data_dir}/ark_data/dump/simu_data_chunk2000/data/$dataset \
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# --split_num $nj
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# 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
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# done
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# for callhome data
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for dset in callhome1_spkall callhome2_spkall; do
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find $data_dir/eval/$dset -maxdepth 1 -type f -exec cp {} {}.1 \;
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output_dir=${data_dir}/ark_data/dump/callhome/$dset
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python local/dump_feature.py \
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--data_dir ${data_dir}/simu/data/${simu_data_dir}/.work \
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--output_dir ${data_dir}/ark_data/dump/simu_data/$dataset \
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--index JOB
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mkdir -p ${data_dir}/ark_data/dump/simu_data/data/$dataset
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--data_dir $data_dir/eval/$dset \
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--output_dir $output_dir \
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--index 1 \
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--num_frames 2000
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mkdir -p ${data_dir}/ark_data/dump/callhome/data/$dset
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python local/gen_feats_scp.py \
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--root_path ${data_dir}/ark_data/dump/simu_data/$dataset \
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--out_path ${data_dir}/ark_data/dump/simu_data/data/$dataset \
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--split_num $nj
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--root_path ${data_dir}/ark_data/dump/callhome/$dset \
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--out_path ${data_dir}/ark_data/dump/callhome/data/$dset \
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--split_num 1
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done
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fi
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