init

download_text.py → download_s2t_metadata.py

@@ -11,8 +11,10 @@ from typing import Optional
 
 import pandas as pd
 
-chunk_size = 10
-url = "https://dl.fbaipublicfiles.com/seamless/data/seamless.dataset.metadata.public.enA-jpn.withduration.tsv.gz"
+direction_speech = os.getenv("DIRECTION_SPEECH", "enA")
+direction_text = os.getenv("DIRECTION_TEXT", "jpn")
+chunk_size = int(os.getenv("CHUNK_SIZE", 10))
+url = f"https://dl.fbaipublicfiles.com/seamless/data/seamless.dataset.metadata.public.{direction_speech}-{direction_text}.withduration.tsv.gz"
 filename = os.path.basename(url)
 subprocess.run(["wget", url, "-O", filename])
 df = pd.read_csv(filename, sep='\t', header=None, dtype=str)
@@ -25,7 +27,7 @@ start = 0
 end = batch_size
 index = 1
 while start != end:
-    df.iloc[start:end].to_csv(f"seamless.dataset.metadata.public.enA-jpn.withduration.reordered.batch_{index}.tsv", sep="\t", index=False, header=False)
+    df.iloc[start:end].to_csv(f"seamless.dataset.metadata.public.{direction_speech}-{direction_text}.withduration.reordered.batch_{index}.tsv", sep="\t", index=False, header=False)
     index += 1
     start = end
     end += batch_size

main_s2t.sh

@@ -1,3 +1,26 @@
+####################
+# 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-jpn: 1_468_292 #
 ######################
@@ -21,36 +44,16 @@ do
   python download_audio.py
 done
 
-# download text
-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}/build/bin/wet_lines"
-cd ../
-wget https://dl.fbaipublicfiles.com/seamless/data/seamless.dataset.metadata.public.enA-jpn.withduration.tsv.gz
-cp ../download_text.py ./
-python download_text.py
-cat seamless.dataset.metadata.public.enA-jpn.withduration.reordered.batch_1.tsv | egrep ^crawl-data | tr '\t' ' ' | wet_lines | tee seamless.dataset.metadata.public.jpn.batch_1.tsv
-cat seamless.dataset.metadata.public.enA-jpn.withduration.reordered.batch_2.tsv | egrep ^crawl-data | tr '\t' ' ' | wet_lines | tee seamless.dataset.metadata.public.jpn.batch_2.tsv
-cat seamless.dataset.metadata.public.enA-jpn.withduration.reordered.batch_3.tsv | egrep ^crawl-data | tr '\t' ' ' | wet_lines | tee seamless.dataset.metadata.public.jpn.batch_3.tsv
-cat seamless.dataset.metadata.public.enA-jpn.withduration.reordered.batch_4.tsv | egrep ^crawl-data | tr '\t' ' ' | wet_lines | tee seamless.dataset.metadata.public.jpn.batch_4.tsv
-cat seamless.dataset.metadata.public.enA-jpn.withduration.reordered.batch_5.tsv | egrep ^crawl-data | tr '\t' ' ' | wet_lines | tee seamless.dataset.metadata.public.jpn.batch_5.tsv
-cat seamless.dataset.metadata.public.enA-jpn.withduration.reordered.batch_6.tsv | egrep ^crawl-data | tr '\t' ' ' | wet_lines | tee seamless.dataset.metadata.public.jpn.batch_6.tsv
-cat seamless.dataset.metadata.public.enA-jpn.withduration.reordered.batch_7.tsv | egrep ^crawl-data | tr '\t' ' ' | wet_lines | tee seamless.dataset.metadata.public.jpn.batch_7.tsv
-cat seamless.dataset.metadata.public.enA-jpn.withduration.reordered.batch_8.tsv | egrep ^crawl-data | tr '\t' ' ' | wet_lines | tee seamless.dataset.metadata.public.jpn.batch_8.tsv
-cat seamless.dataset.metadata.public.enA-jpn.withduration.reordered.batch_9.tsv | egrep ^crawl-data | tr '\t' ' ' | wet_lines | tee seamless.dataset.metadata.public.jpn.batch_9.tsv
-cat seamless.dataset.metadata.public.enA-jpn.withduration.reordered.batch_10.tsv | egrep ^crawl-data | tr '\t' ' ' | wet_lines | tee seamless.dataset.metadata.public.jpn.batch_10.tsv
-cat seamless.dataset.metadata.public.enA-jpn.withduration.reordered.batch_11.tsv | egrep ^crawl-data | tr '\t' ' ' | wet_lines | tee seamless.dataset.metadata.public.jpn.batch_11.tsv
-cp ../format_text.py ./
+# text
+export DIRECTION_SPEECH="enA"
+export DIRECTION_TEXT="jpn"
+export CHUNK_SIZE=10
+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_1.tsv &
+done
 python format_text.py
-mv text.enA-jpn.json ../
-cd ../
-
 
 ########
 # NLLB #