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run.sh
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run.sh
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#source venv/bin/activate
out_file=results_full.csv
nn_experiments=1
gmm_experiments=1
svm_experiments=0
lasso_experiments=1
echo "Extract features"
/repos/kaldi/egs/cancer_30/run_feature.sh stage=-3
array=(4 8 10 12 16 )
printf "model" >> $out_file
printf "\t" >> $out_file
printf "train accuracy" >> $out_file
printf "\t" >> $out_file
printf "train EER" >> $out_file
printf "\t" >> $out_file
printf "test accuracy" >> $out_file
printf "\t" >> $out_file
printf "test EER" >> $out_file
printf "\n" >> $out_file
if [[ $nn_experiments -eq 1 ]]; then
printf "ResNet" >> $out_file
printf "\t" >> $out_file
python train_DNN.py >> $out_file
printf "\n" >> $out_file
fi
if [[ $gmm_experiments -eq 1 ]]; then
for num in ${array[*]}
do
printf "Pitch $num" >> $out_file
printf "\t" >> $out_file
python3 train_GMM.py --train_scp_file="/home/boomkin/repos/kaldi/egs/cancer_30/data/train_pitch/feats.scp" --test_scp_file="/home/boomkin/repos/kaldi/egs/cancer_30/data/test_pitch/feats.scp" --gmm_comps=$num --experiment="gmm_pitch_30sec_${num}_components" --train >> $out_file
done
for num in ${array[*]}
do
printf "PPG $num" >> $out_file
printf "\t" >> $out_file
python3 train_GMM.py --train_scp_file="/home/boomkin/repos/kaldi/egs/cancer_30/data/train_spec_vad/feats.scp" --test_scp_file="/home/boomkin/repos/kaldi/egs/cancer_30/data/test_spec_vad/feats.scp" --train --gmm_comps=$num --experiment="gmm_ppg_30sec_${num}_components" --ppg --no_pause >> $out_file
done
for num in ${array[*]}
do
printf "PLP $num" >> $out_file
printf "\t" >> $out_file
python3 train_GMM.py --train_scp_file="/home/boomkin/repos/kaldi/egs/cancer_30/data/train_plp_vad/feats.scp" --test_scp_file="/home/boomkin/repos/kaldi/egs/cancer_30/data/test_plp_vad/feats.scp" --train --gmm_comps=$num --experiment="gmm_plp_30sec_${num}_components" >> $out_file
done
for num in ${array[*]}
do
printf "PLP DD $num" >> $out_file
printf "\t" >> $out_file
python3 train_GMM.py --train_scp_file="/home/boomkin/repos/kaldi/egs/cancer_30/data/train_plp_vad/feats.scp" --test_scp_file="/home/boomkin/repos/kaldi/egs/cancer_30/data/test_plp_vad/feats.scp" --train --gmm_comps=$num --experiment="gmm_plp_30sec_delta_delta_${num}_components" --delta >> $out_file
done
for num in ${array[*]}
do
printf "MFCC $num" >> $out_file
printf "\t" >> $out_file
python3 train_GMM.py --train_scp_file="/home/boomkin/repos/kaldi/egs/cancer_30/data/train_mfcc_vad/feats.scp" --test_scp_file="/home/boomkin/repos/kaldi/egs/cancer_30/data/test_mfcc_vad/feats.scp" --train --gmm_comps=$num --experiment="gmm_mfcc_30sec_${num}_components" >> $out_file
done
for num in ${array[*]}
do
printf "MFCC DD $num" >> $out_file
printf "\t" >> $out_file
python3 train_GMM.py --train_scp_file="/home/boomkin/repos/kaldi/egs/cancer_30/data/train_mfcc_vad/feats.scp" --test_scp_file="/home/boomkin/repos/kaldi/egs/cancer_30/data/test_mfcc_vad/feats.scp" --train --gmm_comps=$num --experiment="gmm_mfcc_30sec_delta_delta_${num}_components" --delta >> $out_file
done
for num in ${array[*]}
do
printf "LTAS $num" >> $out_file
printf "\t" >> $out_file
python3 train_GMM.py --train_scp_file="/home/boomkin/repos/kaldi/egs/cancer_30/data/train_spec_vad/feats.scp" --test_scp_file="/home/boomkin/repos/kaldi/egs/cancer_30/data/test_spec_vad/feats.scp" --train --gmm_comps=$num --experiment="gmm_ltas_30sec_${num}_components" --ltas >> $out_file
done
fi
if [[ $svm_experiments -eq 1 ]]; then
## SVM experiments
printf "Pitch SVM" >> $out_file
printf "\t" >> $out_file
python3 train_SVM.py --train_scp_file="/home/boomkin/repos/kaldi/egs/cancer_30/data/train_pitch/feats.scp" --test_scp_file="/home/boomkin/repos/kaldi/egs/cancer_30/data/test_pitch/feats.scp" --experiment="svm_pitch_30sec_${num}_components" --train >> $out_file
printf "PPG SVM" >> $out_file
printf "\t" >> $out_file
python3 train_SVM.py --train_scp_file="/home/boomkin/repos/kaldi/egs/cancer_30/data/train_pitch/feats.scp" --test_scp_file="/home/boomkin/repos/kaldi/egs/cancer_30/data/test_pitch/feats.scp" --ppg --experiment="svm_ppg_30sec_${num}_components" --train >> $out_file
printf "Pitch SVM" >> $out_file
printf "\t" >> $out_file
python3 train_SVM.py --train_scp_file="/home/boomkin/repos/kaldi/egs/cancer_30/data/train_pitch/feats.scp" --test_scp_file="/home/boomkin/repos/kaldi/egs/cancer_30/data/test_pitch/feats.scp" --experiment="svm_pitch_30sec_${num}_components" --train >> $out_file
printf "LTAS SVM" >> $out_file
printf "\t" >> $out_file
python3 train_SVM.py --train_scp_file="/home/boomkin/repos/kaldi/egs/cancer_30/data/train_spec_vad/feats.scp" --test_scp_file="/home/boomkin/repos/kaldi/egs/cancer_30/data/test_spec_vad/feats.scp" --ltas --experiment="ltas_pitch_30sec_${num}_components" --train >> $out_file
printf "PLP SVM" >> $out_file
printf "\t" >> $out_file
python3 train_SVM.py --train_scp_file="/home/boomkin/repos/kaldi/egs/cancer_30/data/train_plp_vad/feats.scp" --test_scp_file="/home/boomkin/repos/kaldi/egs/cancer_30/data/test_plp_vad/feats.scp" --train --experiment="svm_plp_30sec_components" >> $out_file
printf "PLP DD" >> $out_file
printf "\t" >> $out_file
python3 train_SVM.py --train_scp_file="/home/boomkin/repos/kaldi/egs/cancer_30/data/train_plp_vad/feats.scp" --test_scp_file="/home/boomkin/repos/kaldi/egs/cancer_30/data/test_plp_vad/feats.scp" --train --experiment="svm_plp_30sec_delta_delta_components" --delta >> $out_file
printf "MFCC" >> $out_file
printf "\t" >> $out_file
python3 train_SVM.py --train_scp_file="/home/boomkin/repos/kaldi/egs/cancer_30/data/train_mfcc_vad/feats.scp" --test_scp_file="/home/boomkin/repos/kaldi/egs/cancer_30/data/test_mfcc_vad/feats.scp" --train --experiment="svm_mfcc_30sec_components" >> $out_file
printf "MFCC DD" >> $out_file
printf "\t" >> $out_file
python3 train_SVM.py --train_scp_file="/home/boomkin/repos/kaldi/egs/cancer_30/data/train_mfcc_vad/feats.scp" --test_scp_file="/home/boomkin/repos/kaldi/egs/cancer_30/data/test_mfcc_vad/feats.scp" --train --experiment="svm_mfcc_30sec_delta_delta_components" --delta >> $out_file
fi
array=(1 0.1 0.01 0.001 0.0001 0.00001 0.000001)
if [[ $lasso_experiments -eq 1 ]]; then
for alpha in ${array[*]}
do
printf "PLP LASSO $alpha" >> $out_file
printf "\t" >> $out_file
python3 train_ARD.py --train_scp_file="/home/boomkin/repos/kaldi/egs/cancer_30/data/train_plp_vad/feats.scp" --test_scp_file="/home/boomkin/repos/kaldi/egs/cancer_30/data/test_plp_vad/feats.scp" --train --experiment="ard_plp_${alpha}_components" --alpha=$alpha >> $out_file
done
for alpha in ${array[*]}
do
printf "LTAS LASSO $alpha" >> $out_file
printf "\t" >> $out_file
python3 train_ARD.py --train_scp_file="/home/boomkin/repos/kaldi/egs/cancer_30/data/train_spec_vad_2/feats.scp" --test_scp_file="/home/boomkin/repos/kaldi/egs/cancer_30/data/test_spec_vad_2/feats.scp" --train --ltas --experiment="ard_ltas_${alpha}_components" --alpha=$alpha >> $out_file
done
for alpha in ${array[*]}
do
printf "PPG LASSO $alpha" >> $out_file
printf "\t" >> $out_file
python3 train_ARD.py --train_scp_file="/home/boomkin/repos/kaldi/egs/cancer_30/data/train_pitch/feats.scp" --test_scp_file="/home/boomkin/repos/kaldi/egs/cancer_30/data/test_pitch/feats.scp" --ppg --experiment="ard_${alpha}_components" --train --no_pause --alpha=$alpha >> $out_file
done
for alpha in ${array[*]}
do
printf "Pitch LASSO $alpha" >> $out_file
printf "\t" >> $out_file
python3 train_ARD.py --train_scp_file="/home/boomkin/repos/kaldi/egs/cancer_30/data/train_pitch/feats.scp" --test_scp_file="/home/boomkin/repos/kaldi/egs/cancer_30/data/test_pitch/feats.scp" --experiment="ard_pitch_${alpha}_components" --train --alpha=$alpha >> $out_file
done
for alpha in ${array[*]}
do
printf "MFCC LASSO $alpha" >> $out_file
printf "\t" >> $out_file
python3 train_ARD.py --train_scp_file="/home/boomkin/repos/kaldi/egs/cancer_30/data/train_mfcc_vad/feats.scp" --test_scp_file="/home/boomkin/repos/kaldi/egs/cancer_30/data/test_mfcc_vad/feats.scp" --experiment="ard_mfcc_${alpha}_components" --train --alpha=$alpha >> $out_file
done
fi
#train_GMM.py--train_scp_file="/home/boomkin/repos/kaldi/egs/cancer_30/data/train_spec_vad/feats.scp" --test_scp_file="/home/boomkin/repos/kaldi/egs/cancer_30/data/test_spec_vad/feats.scp" --train --gmm_comps=16 --experiment="gmm_ltas_30sec"