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extract_feats.sh
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extract_feats.sh
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#!/bin/bash
# This script extracts Spec, CQT, LFCC features for:
# ASVspoof2019 PA train, PA dev, PA eval, LA train, LA dev, LA eval
. ./cmd.sh
. ./path.sh
set -e
specdir=`pwd`/raw_feats/spec
datadir=/home/rostami/DS_10283_3336/
stage=3
. ./parse_options.sh
mkdir -p data/PA_train data/PA_dev data/PA_eval data/LA_train data/LA_dev data/LA_eval
if [ $stage -le 0 ]; then
echo "Stage 0: prepare dataset."
for access_type in PA LA;do
protofile=$datadir/${access_type}/ASVspoof2019_${access_type}_cm_protocols/ASVspoof2019.${access_type}.cm.train.trn.txt
awk '{print $2" "$4}' $protofile >data/${access_type}_train/utt2systemID
awk '{print $2" "$1}' $protofile >data/${access_type}_train/utt2spk
feats_extraction/utt2spk_to_spk2utt.pl data/${access_type}_train/utt2spk >data/${access_type}_train/spk2utt
awk -v dir="${datadir}/${access_type}" -v type="${access_type}_train" '{print $2" sox "dir"/ASVspoof2019_"type"/flac/"$2".flac -t wav - |"}' $protofile >data/${access_type}_train/wav.scp
for dataset in dev eval;do
protofile=$datadir/${access_type}/ASVspoof2019_${access_type}_cm_protocols/ASVspoof2019.${access_type}.cm.${dataset}.trl.txt
awk '{print $2" "$4}' $protofile >data/${access_type}_${dataset}/utt2systemID
awk '{print $2" "$1}' $protofile >data/${access_type}_${dataset}/utt2spk
feats_extraction/utt2spk_to_spk2utt.pl data/${access_type}_${dataset}/utt2spk >data/${access_type}_${dataset}/spk2utt
awk -v dir="${datadir}/${access_type}" -v type="${access_type}_${dataset}" '{print $2" sox "dir"/ASVspoof2019_"type"/flac/"$2".flac -t wav - |"}' $protofile >data/${access_type}_${dataset}/wav.scp
done
done
echo "dataset finished"
fi
if [ $stage -le 1 ]; then
echo "Stage 1: extract Spec feats."
mkdir -p data/spec
for name in PA_train PA_dev PA_eval LA_train LA_dev LA_eval; do
[ -d data/spec/${name} ] cp -r data/${name} data/spec/${name}
feats_extraction/make_spectrogram.sh --feats-config conf/feats/spec.conf --nj 80 --cmd "$train_cmd" \
data/spec/${name} exp/make_spec $specdir
done
echo "Spec feats done"
fi
if [ $stage -le 2 ]; then
echo "Stage 2: extract CQT feats."
python3 -W ignore feats_extraction/compute_CQT.py --out_dir data/cqt --access_type PA --param_json_path conf/feats/cqt_48bpo_fmin15.json --num_workers 60
# python3 feats_extraction/compute_CQT.py --out_dir data/cqt --access_type LA --param_json_path conf/feats/cqt_48bpo_fmin15.json --num_workers 60
python3 -W ignore feats_extraction/GenLPCQTFeats_kald
i.py --access_type PA --work_dir data/cqt
# python3 feats_extraction/GenLPCQTFeats_kaldi.py --access_type LA --work_dir data/cqt
echo "DONE stage 2"
# uncomment below for removing numpy data to save space.
#for name in PA_train PA_dev PA_eval LA_train LA_dev LA_eval; do
# rm -rf data/cqt/${name}/*.npy
#done
# find data/cqt/ -type f -name "*.npy" -exec rm {} \;
fi
if [ $stage -le 3 ]; then
echo "Stage 3: truncate features and generate labels."
for name in PA_train PA_dev; do
for feat_type in cqt; do
echo "Processing $name $feat_type"
python3 feats_extraction/feat_slicing.py --in-scp data/${feat_type}/${name}/feats.scp --out-scp data/${feat_type}/${name}/feats_slicing.scp --out-ark data/${feat_type}/${name}/feats_slicing.ark
python3 feats_extraction/convertID2index.py --scp-file data/${feat_type}/${name}/feats_slicing.scp --sysID-file data/${name}/utt2systemID --out-file data/${name}/utt2index --access-type ${name:0:2}
done
done
fi
# #!/bin/bash
# # This script extracts Spec, CQT, LFCC features for:
# # ASVspoof2019 PA train, PA dev, PA eval, LA train, LA dev, LA eval
# . ./cmd.sh
# . ./path.sh
# set -e
# specdir=`pwd`/raw_feats/spec
# datadir=/home/rostami/DS_10283_3336
# stage=3
# # . ./parse_options.sh
# mkdir -p data/PA_train data/PA_dev data/PA_eval data/LA_train data/LA_dev data/LA_eval
# if [ $stage -le 0 ]; then
# echo "Stage 0: prepare dataset."
# for access_type in PA LA;do
# protofile=$datadir/${access_type}/ASVspoof2019_${access_type}_cm_protocols/ASVspoof2019.${access_type}.cm.train.trn.txt
# awk '{print $2" "$4}' $protofile >data/${access_type}_train/utt2systemID
# awk '{print $2" "$1}' $protofile >data/${access_type}_train/utt2spk
# feats_extraction/utt2spk_to_spk2utt.pl data/${access_type}_train/utt2spk >data/${access_type}_train/spk2utt
# awk -v dir="${datadir}/${access_type}" -v type="${access_type}_train" '{print $2" sox "dir"/ASVspoof2019_"type"/flac/"$2".flac -t wav - |"}' $protofile >data/${access_type}_train/wav.scp
# for dataset in dev eval;do
# protofile=$datadir/${access_type}/ASVspoof2019_${access_type}_cm_protocols/ASVspoof2019.${access_type}.cm.${dataset}.trl.txt
# awk '{print $2" "$4}' $protofile >data/${access_type}_${dataset}/utt2systemID
# awk '{print $2" "$1}' $protofile >data/${access_type}_${dataset}/utt2spk
# feats_extraction/utt2spk_to_spk2utt.pl data/${access_type}_${dataset}/utt2spk >data/${access_type}_${dataset}/spk2utt
# awk -v dir="${datadir}/${access_type}" -v type="${access_type}_${dataset}" '{print $2" sox "dir"/ASVspoof2019_"type"/flac/"$2".flac -t wav - |"}' $protofile >data/${access_type}_${dataset}/wav.scp
# done
# done
# echo "dataset finished"
# #
# fi
# if [ $stage -le 1 ]; then
# echo "Stage 1: extract Spec feats."
# mkdir -p data/spec
# for name in PA_train PA_dev PA_eval LA_train LA_dev LA_eval; do
# [ -d data/spec/${name} ] cp -r data/${name} data/spec/${name}
# feats_extraction/make_spectrogram.sh --feats-config conf/feats/spec.conf --nj 80 --cmd "$train_cmd" \
# data/spec/${name} exp/make_spec $specdir
# done
# echo "Spec feats done"
# #
# fi
# if [ $stage -le 2 ]; then
# echo "Stage 2: extract CQT feats."
# python3 -W ignore feats_extraction/compute_CQT.py --out_dir /home/rostami/cqt --access_type PA --param_json_path conf/feats/cqt_48bpo_fmin15.json --num_workers 60
# # python3 feats_extraction/compute_CQT.py --out_dir data/cqt --access_type LA --param_json_path conf/feats/cqt_48bpo_fmin15.json --num_workers 60
# python3 -W ignore feats_extraction/GenLPCQTFeats_kaldi.py --access_type PA --work_dir /home/rostami/cqt
# # python3 feats_extraction/GenLPCQTFeats_kaldi.py --access_type LA --work_dir data/cqt
# # # uncomment below for removing numpy data to save space.
# # find /home/rostami/cqt/ -maxdepth 2 -type f -name "*.npy" -delete
# #
# fi
# if [ $stage -le 3 ]; then
# echo "Stage 3: truncate features and generate labels."
# for name in PA_dev PA_train; do
# for feat_type in cqt; do
# echo "Processing $name $feat_type"
# python3 feats_extraction/feat_slicing.py --in-scp /home/rostami/${feat_type}/${name}/feats.scp --out-scp /home/rostami/${feat_type}/${name}/feats_slicing.scp --out-ark /home/rostami/${feat_type}/${name}/feats_slicing.ark
# # echo "python3 feats_extraction/convertID2index.py --scp-file data/${feat_type}/${name}/feats_slicing.scp --sysID-file data/${feat_type}/${name}/utt2systemID --out-file data/${feat_type}/${name}/utt2index --access-type ${name:0:2}"
# # python3 feats_extraction/convertID2index.py --scp-file /home/rostami/${feat_type}/${name}/feats_slicing.scp --sysID-file /home/rostami/${feat_type}/${name}/utt2systemID --out-file /home/rostami/${feat_type}/${name}/utt2index --access-type ${name:0:2}
# done
# done
# #
# fi