File size: 2,679 Bytes
3622be8 c76e8c8 ea85278 c76e8c8 6c57588 85389e6 6c57588 c76e8c8 ea85278 2ace478 436c948 2ace478 d094b53 ea85278 54f280d d094b53 54f280d 436c948 54f280d c76e8c8 54f280d |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 |
####################
# Install Wet Tool #
####################
# libraries for runpod
sudo apt-get install libcurl4-openssl-dev
sudo apt-get install libbz2-dev
sudo apt-get install liblzma-dev
sudo add-apt-repository ppa:boost-latest/ppa -y
sudo apt-get update
sudo apt-get purge boost* -y
sudo apt-get install libboost-all-dev -y
# clone and build the library
git clone https://github.com/kpu/preprocess
cd preprocess
git checkout wet
git submodule update --init --recursive
mkdir build
cd build
cmake ..
make -j4
alias wet_lines="${PWD}/bin/wet_lines"
cd ../../
###########
# enA-vie #
###########
# text
export DIRECTION_SPEECH="enA"
export DIRECTION_TEXT="vie"
export CHUNK_SIZE=20
python download_s2t_metadata.py
for i in $(seq 1 ${CHUNK_SIZE});
do
cat seamless.dataset.metadata.public.${DIRECTION_SPEECH}-${DIRECTION_TEXT}.withduration.reordered.batch_${i}.tsv | egrep ^crawl-data | tr '\t' ' ' | wet_lines | tee metadata.${DIRECTION_SPEECH}-${DIRECTION_TEXT}.batch_${i}.tsv &
done
python format_text.py
###########
# enA-est #
###########
# text
export DIRECTION_SPEECH="enA"
export DIRECTION_TEXT="est"
export CHUNK_SIZE=20
python download_s2t_metadata.py
for i in $(seq 1 ${CHUNK_SIZE});
do
cat seamless.dataset.metadata.public.${DIRECTION_SPEECH}-${DIRECTION_TEXT}.withduration.reordered.batch_${i}.tsv | egrep ^crawl-data | tr '\t' ' ' | wet_lines | tee metadata.${DIRECTION_SPEECH}-${DIRECTION_TEXT}.batch_${i}.tsv &
done
python format_text.py
# audio
for i in $(seq 213 300);
do
export N_POOL=15
export DATASET_ID=${i}
export DIRECTION_SPEECH="enA"
export DIRECTION_TEXT="est"
export LINE_NO_START=$(((DATASET_ID-1) * 2500))
export LINE_NO_END=$((DATASET_ID * 2500))
echo ${LINE_NO_START}
python fetch_dataset_s2t.py
done
###########
# enA-jpn #
###########
# text
export DIRECTION_SPEECH="enA"
export DIRECTION_TEXT="jpn"
export CHUNK_SIZE=20
python download_s2t_metadata.py
for i in $(seq 1 ${CHUNK_SIZE});
do
cat seamless.dataset.metadata.public.${DIRECTION_SPEECH}-${DIRECTION_TEXT}.withduration.reordered.batch_${i}.tsv | egrep ^crawl-data | tr '\t' ' ' | wet_lines | tee metadata.${DIRECTION_SPEECH}-${DIRECTION_TEXT}.batch_${i}.tsv &
done
python format_text.py
# audio
for i in $(seq 233 294);
do
export N_POOL=15
export DATASET_ID=${i}
export DIRECTION_SPEECH="enA"
export DIRECTION_TEXT="jpn"
export LINE_NO_START=$(((DATASET_ID-1) * 2500))
export LINE_NO_END=$((DATASET_ID * 2500))
echo ${LINE_NO_START}
python fetch_dataset_s2t.py
done
########
# NLLB #
########
# https://www.kecl.ntt.co.jp/icl/lirg/jparacrawl/
python -c "from datasets import load_dataset; load_dataset('allenai/nllb', 'eng_Latn-jpn_Jpan')"
|