init

delete_audio.py

@@ -1,15 +0,0 @@
-import os
-from os.path import join as p_join
-from glob import glob
-from tqdm import tqdm
-
-direction = os.getenv("DIRECTION", "enA-jaA")
-cache_dir_audio = p_join("download", "audio", direction)
-cache_dir_feature = p_join("download", "feature", direction)
-line_no_start = int(os.getenv("LINE_NO_START", 0))
-line_no_end = int(os.getenv("LINE_NO_END", 10000))
-for i in tqdm(range(line_no_start, line_no_end), total=line_no_end-line_no_start):
-    for audio_file in glob(p_join(cache_dir_audio, "*", f"{i}.*")):
-        os.remove(audio_file)
-    if os.path.exists(p_join(cache_dir_feature, f"{i}.json")):
-        os.remove(p_join(cache_dir_feature, f"{i}.json"))

fetch_dataset_s2s.py

@@ -0,0 +1,206 @@
+import json
+import os
+import tarfile
+import zipfile
+import gzip
+import subprocess
+from os.path import join as p_join
+from math import ceil, floor
+from tqdm import tqdm
+from multiprocessing import Pool
+from typing import Optional, Dict
+from glob import glob
+# import librosa
+
+import pandas as pd
+import soundfile as sf
+from datasets import Dataset, Audio, DatasetDict
+
+audio_loader = Audio()
+# dataset config
+url_metadata_dict = {
+    "enA-jaA": "https://dl.fbaipublicfiles.com/seamless/data/seamless_align_nov2023_extension/seamless.dataset.metadata.public.enA-jaA.tsv.gz",
+    "enA-zhA": "https://dl.fbaipublicfiles.com/seamless/data/seamless_align_nov2023_extension/seamless.dataset.metadata.public.enA-zhA.tsv.gz",
+    "enA-viA": "https://dl.fbaipublicfiles.com/seamless/data/seamless_align_nov2023_extension/seamless.dataset.metadata.public.enA-viA.tsv.gz",
+}
+direction = os.getenv("DIRECTION", "enA-jaA")
+if direction not in url_metadata_dict:
+    a, b = direction.split("-")
+    url_metadata_dict[direction] = f"https://dl.fbaipublicfiles.com/seamless/data/seamless_align_nov2023_extension/seamless.dataset.metadata.public.{a}-{b}.tsv.gz"
+sides = set(direction.split("-"))
+cache_dir_audio = p_join("download", "audio", direction)
+cache_dir_feature = p_join("download", "feature", direction)
+os.makedirs(cache_dir_feature, exist_ok=True)
+for s in sides:
+    os.makedirs(p_join(cache_dir_audio, s), exist_ok=True)
+# processor config
+n_pool = int(os.getenv("N_POOL", 1))
+wget_max_retry = os.getenv("MAX_RETRY", "2")
+wget_timeout = os.getenv("TIMEOUT", "20")
+line_no_start = int(os.getenv("LINE_NO_START", 0))
+line_no_end = int(os.getenv("LINE_NO_END", 10000))
+dataset_id = os.getenv("DATASET_ID", 0)
+hf_org = os.getenv("HF_ORG", "asahi417")
+hf_dataset = f"seamless-align-{direction}"
+skip_download = bool(int(os.getenv("SKIP_DOWNLOAD", 0)))
+sampling_rate = 16000  # seamless-align aligns audio in 16kHz
+
+
+def wget(url: str, output_file: Optional[str] = None):
+    os.makedirs(os.path.dirname(output_file), exist_ok=True)
+    subprocess.run(["wget", url, "-O", output_file, "--tries", wget_max_retry, "--timeout", wget_timeout])
+    if not os.path.exists(output_file):
+        return False
+    if output_file.endswith('.tar.gz') or output_file.endswith('.tgz') or output_file.endswith('.tar'):
+        if output_file.endswith('.tar'):
+            tar = tarfile.open(output_file)
+        else:
+            tar = tarfile.open(output_file, "r:gz")
+        tar.extractall(os.path.dirname(output_file))
+        tar.close()
+        os.remove(output_file)
+    elif output_file.endswith('.gz'):
+        with gzip.open(output_file, 'rb') as f:
+            with open(output_file.replace('.gz', ''), 'wb') as f_write:
+                f_write.write(f.read())
+        os.remove(output_file)
+    elif output_file.endswith('.zip'):
+        with zipfile.ZipFile(output_file, 'r') as zip_ref:
+            zip_ref.extractall()
+        os.remove(output_file)
+    return True
+
+
+def get_metadata():
+    url_metadata = url_metadata_dict[direction]
+    meta_data_filename = os.path.basename(url_metadata)
+    meta_data_path = p_join("download", "meta", meta_data_filename)
+    if not os.path.exists(meta_data_path.replace(".gz", "")):
+        assert wget(url_metadata, output_file=meta_data_path)
+    df = pd.read_csv(meta_data_path.replace(".gz", ""), sep=r'[\t\s]', header=None)
+    df = df[[0, 2, 3, 4, 9, 10, 11, 12]]
+    df.columns = ["id", "url", "duration_start", "duration_end", "laser_score", "direction", "side", "line_no"]
+    if direction == "enA-jpn":
+        df = df[df["side"] == "enA"]
+    assert len(df["direction"].unique()) == 1
+    df.pop("direction")
+    return df.sort_values(by=["line_no", "side"])
+
+
+def to_json_serializable(val):
+    if "float" in str(type(val)):
+        return float(val)
+    if "int" in str(type(val)):
+        return int(val)
+    return str(val)
+
+
+def cleanup(features, feature_file):
+    if os.path.exists(feature_file):
+        os.remove(feature_file)
+    for _side in sides:
+        for _unrelated_audio_file in glob(p_join(cache_dir_audio, _side, f"{features['line_no']}.*")):
+            os.remove(_unrelated_audio_file)
+    # create a dummy so that we can skip from next run
+    with open(feature_file, "w") as f:
+        json.dump({"dummy": "dummy"}, f)
+
+
+def get_audio(dataframe: pd.DataFrame):
+    resampler = {}
+    features = {"line_no": int(dataframe.pop('line_no').values[0])}
+    feature_file = p_join(cache_dir_feature, f'{features["line_no"]}.json')
+    for side, df in dataframe.groupby("side"):
+        df.pop("side")
+        features.update({f"{side}.{k}": to_json_serializable(v) for k, v in df.iloc[0].to_dict().items()})
+        identifier = os.path.basename(features[f"{side}.url"]).split(".")[-1]
+        features[f"{side}.path"] = str(p_join(cache_dir_audio, side, f"{features['line_no']}.{identifier}"))
+        start, end = features[f"{side}.duration_start"], features[f"{side}.duration_end"]
+        if not os.path.exists(features[f"{side}.path"]):
+            print(f"WGET {features[f'{side}.url']}")
+            flag = wget(features[f"{side}.url"], output_file=features[f"{side}.path"])
+            if not flag:
+                print("\n#### ERROR: wget failure ####\n")
+                cleanup(features, feature_file)
+                return None
+            else:
+                try:
+                    print(f"LOAD AUDIO FROM {features[f'{side}.path']}")
+                    wav, sr = sf.read(features[f"{side}.path"])
+                    print(f"wav shape:{wav.shape}")
+                    if wav.ndim > 1:
+                        wav = wav[:, 0]
+                    wav = wav[floor(start / sampling_rate * sr):ceil(end / sampling_rate * sr)]
+                    print(f"wav shape (after truncate):{wav.shape}")
+                    wav = wav[:int(end/sampling_rate * sr) + sr]
+                    print(f"SAVING: {features[f'{side}.path']}")
+                    sf.write(features[f"{side}.path"], wav, sr)
+                    # if sr != sampling_rate:
+                    #     print(f"RESAMPLING: {wav.shape} length audio")
+                    #     wav = librosa.resample(wav, orig_sr=sr, target_sr=sampling_rate)
+                    # sf.write(features[f"{side}.path"], wav[start:end], sampling_rate)
+
+                except Exception as e:
+                    print(f"\n#### ERROR ####\n {e}")
+                    cleanup(features, feature_file)
+                    return None
+    print(f"\n### SUCCESS! ###\n:{features['line_no']}")
+    with open(feature_file, "w") as f:
+        json.dump(features, f)
+    return features["line_no"]
+
+
+def loader(feature: str) -> Dict:
+    with open(feature) as f_reader:
+        return json.load(f_reader)
+
+
+if __name__ == '__main__':
+    if not skip_download:
+        df_metadata = get_metadata()
+        print(f"metadata: {len(df_metadata)}, {line_no_start} --> {line_no_end}")
+        inputs = [
+            g for line_no, g in df_metadata.groupby("line_no")
+            if line_no_start <= line_no < line_no_end and not os.path.exists(
+                p_join(cache_dir_feature, f'{int(line_no)}.json')
+            )
+        ]
+        print(f"filtered unique lines: {len(inputs)}")
+        inputs = [g for g in inputs if len(g["side"].unique()) == 2 and set(g["side"].unique()) == sides]
+        print(f"removed side != 2: {len(inputs)}")
+
+        if n_pool == 1:
+            for g in tqdm(inputs, total=len(inputs)):
+                line_no = get_audio(g)
+        else:
+            with Pool(n_pool) as pool:
+                for line_no in pool.imap_unordered(get_audio, inputs):
+                    if line_no:
+                        print(line_no)
+
+    print("UPLOADING TO HF!!!")
+    features = [p_join(cache_dir_feature, f'{i}.json') for i in range(line_no_start, line_no_end)]
+    print(f"- raw feature: {len(features)}")
+    features = [i for i in features if os.path.exists(i)]
+    print(f"- path exists: {len(features)}")
+    features = [loader(i) for i in features]
+    features = [i for i in features if "dummy" not in i]
+    print(f"- dummy removed: {len(features)}")
+    print(f"push {len(features)} records to hub")
+    data_dict = {}
+    for side in sides:
+        data_dict.update({f"{side}.audio": [i.pop(f"{side}.path") for i in features]})
+    data_dict.update({k: [i[k] for i in features] for k in features[0].keys()})
+    audio_dataset = Dataset.from_dict(data_dict)
+    for side in sides:
+        audio_dataset = audio_dataset.cast_column(f"{side}.audio", Audio())
+    DatasetDict({"train": audio_dataset}).push_to_hub(
+        f"{hf_org}/{hf_dataset}",
+        config_name=f"subset_{dataset_id}"
+    )
+    print("clear the workspace")
+    for i in tqdm(range(line_no_start, line_no_end), total=line_no_end - line_no_start):
+        for audio_file in glob(p_join(cache_dir_audio, "*", f"{i}.*")):
+            os.remove(audio_file)
+        if os.path.exists(p_join(cache_dir_feature, f"{i}.json")):
+            os.remove(p_join(cache_dir_feature, f"{i}.json"))

main.sh

@@ -1,256 +0,0 @@
-export CUDA_VISIBLE_DEVICES=0
-export CUDA_VISIBLE_DEVICES=1
-rm -rf download/audio
-rm -rf download/feature
-python -c 'n=41; import os; from glob import glob; tmp = [int(os.path.basename(i).split(".")[0]) for i in glob("download/feature/enA-jaA/*.json")]; print(len([x for x in tmp if (n-1) * 2500 <= x < n * 2500]))'
-python -c 'n=41; import os; from glob import glob; tmp = [int(os.path.basename(i).split(".")[0]) for i in glob("download/audio/enA-jaA/enA/*")]; print(len([x for x in tmp if (n-1) * 2500 <= x < n * 2500]))'
-python -c 'n=41; import os; from glob import glob; tmp = [int(os.path.basename(i).split(".")[0]) for i in glob("download/audio/enA-jaA/jaA/*")]; print(len([x for x in tmp if (n-1) * 2500 <= x < n * 2500]))'
-python -c 'n=42; import os; from glob import glob; tmp = [int(os.path.basename(i).split(".")[0]) for i in glob("download/feature/enA-jaA/*.json")]; print(len([x for x in tmp if (n-1) * 2500 <= x < n * 2500]))'
-python -c 'n=42; import os; from glob import glob; tmp = [int(os.path.basename(i).split(".")[0]) for i in glob("download/audio/enA-jaA/enA/*")]; print(len([x for x in tmp if (n-1) * 2500 <= x < n * 2500]))'
-python -c 'n=42; import os; from glob import glob; tmp = [int(os.path.basename(i).split(".")[0]) for i in glob("download/audio/enA-jaA/jaA/*")]; print(len([x for x in tmp if (n-1) * 2500 <= x < n * 2500]))'
-python -c 'n=51; import os; from glob import glob; tmp = [int(os.path.basename(i).split(".")[0]) for i in glob("download/feature/enA-jaA/*.json")]; print(len([x for x in tmp if (n-1) * 2500 <= x < n * 2500]))'
-python -c 'n=51; import os; from glob import glob; tmp = [int(os.path.basename(i).split(".")[0]) for i in glob("download/audio/enA-jaA/enA/*")]; print(len([x for x in tmp if (n-1) * 2500 <= x < n * 2500]))'
-python -c 'n=51; import os; from glob import glob; tmp = [int(os.path.basename(i).split(".")[0]) for i in glob("download/audio/enA-jaA/jaA/*")]; print(len([x for x in tmp if (n-1) * 2500 <= x < n * 2500]))'
-
-python -c 'n=1; import os; from glob import glob; tmp = [int(os.path.basename(i).split(".")[0]) for i in glob("download/feature/enA-jaA/*.json")]; print(len([x for x in tmp if (n-1) * 2500 <= x < n * 2500]))'
-python -c 'n=1; import os; from glob import glob; tmp = [int(os.path.basename(i).split(".")[0]) for i in glob("download/audio/enA-jaA/enA/*")]; print(len([x for x in tmp if (n-1) * 2500 <= x < n * 2500]))'
-python -c 'n=1; import os; from glob import glob; tmp = [int(os.path.basename(i).split(".")[0]) for i in glob("download/audio/enA-jaA/jaA/*")]; print(len([x for x in tmp if (n-1) * 2500 <= x < n * 2500]))'
-python -c 'n=2; import os; from glob import glob; tmp = [int(os.path.basename(i).split(".")[0]) for i in glob("download/feature/enA-jaA/*.json")]; print(len([x for x in tmp if (n-1) * 2500 <= x < n * 2500]))'
-python -c 'n=2; import os; from glob import glob; tmp = [int(os.path.basename(i).split(".")[0]) for i in glob("download/audio/enA-jaA/enA/*")]; print(len([x for x in tmp if (n-1) * 2500 <= x < n * 2500]))'
-python -c 'n=2; import os; from glob import glob; tmp = [int(os.path.basename(i).split(".")[0]) for i in glob("download/audio/enA-jaA/jaA/*")]; print(len([x for x in tmp if (n-1) * 2500 <= x < n * 2500]))'
-python -c 'n=3; import os; from glob import glob; tmp = [int(os.path.basename(i).split(".")[0]) for i in glob("download/feature/enA-jaA/*.json")]; print(len([x for x in tmp if (n-1) * 2500 <= x < n * 2500]))'
-python -c 'n=3; import os; from glob import glob; tmp = [int(os.path.basename(i).split(".")[0]) for i in glob("download/audio/enA-jaA/enA/*")]; print(len([x for x in tmp if (n-1) * 2500 <= x < n * 2500]))'
-python -c 'n=3; import os; from glob import glob; tmp = [int(os.path.basename(i).split(".")[0]) for i in glob("download/audio/enA-jaA/jaA/*")]; print(len([x for x in tmp if (n-1) * 2500 <= x < n * 2500]))'
-
-python -c 'file_name="tmp.mp3"; from datasets import Audio; a=Audio(); wav=a.decode_example({"path": file_name, "bytes": None}); print(wav)'
-
-####################
-# enA-jaA: 718_606 #
-####################
-# test
-export DATASET_ID=test
-export DIRECTION="enA-jaA"
-export LINE_NO_START=0
-export LINE_NO_END=10
-python download_audio.py
-
-# main
-for i in $(seq 1 144);
-do
-  export N_POOL=15
-  export DATASET_ID=${i}
-  export DIRECTION="enA-jaA"
-  export LINE_NO_START=$(((DATASET_ID-1) * 2500))
-  export LINE_NO_END=$((DATASET_ID * 2500))
-  echo ${LINE_NO_START}
-  python download_audio.py
-done
-
-####################
-# enA-zhA: 1_289_192 #
-####################
-# test
-export DATASET_ID=test
-export DIRECTION="enA-zhA"
-export LINE_NO_START=0
-export LINE_NO_END=10
-python download_audio.py
-
-####################
-# enA-viA: 740_598 #
-####################
-# test
-export DATASET_ID=test
-export DIRECTION="enA-viA"
-export LINE_NO_START=0
-export LINE_NO_END=10
-python download_audio.py
-
-####################
-# enA-koA: 511_358 #
-####################
-# test
-export DATASET_ID=test
-export DIRECTION="enA-koA"
-export LINE_NO_START=0
-export LINE_NO_END=10
-python download_audio.py
-
-####################
-# enA-hiA:  #
-####################
-# test
-export DATASET_ID=test
-export DIRECTION="enA-hiA"
-export LINE_NO_START=0
-export LINE_NO_END=10
-python download_audio.py
-
-####################
-# enA-deA: 511_358 #
-####################
-# test
-export DATASET_ID=test
-export DIRECTION="enA-frA"
-export LINE_NO_START=0
-export LINE_NO_END=10
-python download_audio.py
-
-
-######################
-# enA-jpn: 1_468_292 #
-######################
-# test
-export DATASET_ID=test
-export DIRECTION="enA-jaA"
-export LINE_NO_START=0
-export LINE_NO_END=10
-python download_audio.py
-
-
-# DOWNLOAD AUDIO
-for i in $(seq 91 100);
-do
-  export N_POOL=15
-  export DATASET_ID=${i}
-  export DIRECTION="enA-jpn"
-  export LINE_NO_START=$(((DATASET_ID-1) * 2500))
-  export LINE_NO_END=$((DATASET_ID * 2500))
-  echo ${LINE_NO_START}
-  python download_audio.py
-done
-
-
-export DIRECTION="enA-jpn"
-export LINE_NO_START=0
-export LINE_NO_END=50000
-python download_audio.py
-
-export DIRECTION="enA-jpn"
-export LINE_NO_START=50000
-export LINE_NO_END=100000
-python download_audio.py
-
-export DIRECTION="enA-jpn"
-export LINE_NO_START=100000
-export LINE_NO_END=150000
-python download_audio.py
-
-export DIRECTION="enA-jpn"
-export LINE_NO_START=150000
-export LINE_NO_END=300000
-python download_audio.py
-
-export DIRECTION="enA-jpn"
-export LINE_NO_START=300000
-export LINE_NO_END=360000
-python download_audio.py
-
-
-# FILTER AUDIO
-export DIRECTION="enA-jpn"
-export DIRECTION_SPEECH="enA"
-export LINE_NO_START=0
-export LINE_NO_END=25000
-python filter_audio.py
-
-export DIRECTION="enA-jpn"
-export DIRECTION_SPEECH="enA"
-export LINE_NO_START=25000
-export LINE_NO_END=50000
-python filter_audio.py
-
-export DIRECTION="enA-jpn"
-export DIRECTION_SPEECH="enA"
-export LINE_NO_START=50000
-export LINE_NO_END=75000
-python filter_audio.py
-
-export DIRECTION="enA-jpn"
-export DIRECTION_SPEECH="enA"
-export LINE_NO_START=75000
-export LINE_NO_END=100000
-python filter_audio.py
-
-export DIRECTION="enA-jpn"
-export DIRECTION_SPEECH="enA"
-export LINE_NO_START=100000
-export LINE_NO_END=125000
-python filter_audio.py
-
-export DIRECTION="enA-jpn"
-export DIRECTION_SPEECH="enA"
-export LINE_NO_START=125000
-export LINE_NO_END=150000
-python filter_audio.py
-
-export DIRECTION="enA-jpn"
-export DIRECTION_SPEECH="enA"
-export LINE_NO_START=150000
-export LINE_NO_END=175000
-python filter_audio.py
-
-export DIRECTION="enA-jpn"
-export DIRECTION_SPEECH="enA"
-export LINE_NO_START=175000
-export LINE_NO_END=200000
-python filter_audio.py
-
-
-export DIRECTION="enA-jpn"
-export DIRECTION_SPEECH="enA"
-export LINE_NO_START=200000
-export LINE_NO_END=225000
-python filter_audio.py
-
-#
-#export LINE_NO_START=150000
-#export LINE_NO_END=300000
-#export DATASET_ID="0"
-#python push_s2t_translation.py
-#
-#
-#export LINE_NO_START=300000
-#export LINE_NO_END=360000
-#export DATASET_ID="0"
-#python push_s2t_translation.py
-
-
-
-# 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 ./
-python format_text.py
-mv text.enA-jpn.json ../
-cd ../
-
-
-########
-# 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')"
-

main_s2s.sh

@@ -0,0 +1,101 @@
+####################
+# enA-jaA: 718_606 #
+####################
+# test
+export DATASET_ID=test
+export DIRECTION="enA-jaA"
+export LINE_NO_START=0
+export LINE_NO_END=10
+python fetch_dataset_s2s.py
+# main
+for i in $(seq 1 144);
+do
+  export N_POOL=15
+  export DATASET_ID=${i}
+  export DIRECTION="enA-jaA"
+  export LINE_NO_START=$(((DATASET_ID-1) * 2500))
+  export LINE_NO_END=$((DATASET_ID * 2500))
+  echo ${LINE_NO_START}
+  python fetch_dataset_s2s.py
+done
+
+######################
+# enA-zhA: 1_289_192 #
+######################
+# test
+export DATASET_ID=test
+export DIRECTION="enA-zhA"
+export LINE_NO_START=0
+export LINE_NO_END=10
+python fetch_dataset_s2s.py
+
+####################
+# enA-viA: 740_598 #
+####################
+# test
+export DATASET_ID=test
+export DIRECTION="enA-viA"
+export LINE_NO_START=0
+export LINE_NO_END=10
+python fetch_dataset_s2s.py
+# main
+for i in $(seq 1 40);
+do
+  export N_POOL=15
+  export DATASET_ID=${i}
+  export DIRECTION="enA-viA"
+  export LINE_NO_START=$(((DATASET_ID-1) * 2500))
+  export LINE_NO_END=$((DATASET_ID * 2500))
+  echo ${LINE_NO_START}
+  python fetch_dataset_s2s.py
+done
+
+####################
+# enA-koA: 511_358 #
+####################
+# test
+export DATASET_ID=test
+export DIRECTION="enA-koA"
+export LINE_NO_START=0
+export LINE_NO_END=10
+python fetch_dataset_s2s.py
+
+####################
+# enA-hiA: 454_942 #
+####################
+# test
+export DATASET_ID=test
+export DIRECTION="enA-hiA"
+export LINE_NO_START=0
+export LINE_NO_END=10
+python fetch_dataset_s2s.py
+
+######################
+# enA-frA: 3_054_258 #
+######################
+# test
+export DATASET_ID=test
+export DIRECTION="enA-frA"
+export LINE_NO_START=0
+export LINE_NO_END=10
+python fetch_dataset_s2s.py
+
+######################
+# enA-esA: 2_658_022 #
+######################
+# test
+export DATASET_ID=test
+export DIRECTION="enA-esA"
+export LINE_NO_START=0
+export LINE_NO_END=10
+python fetch_dataset_s2s.py
+
+######################
+# enA-deA: 1_965_186 #
+######################
+# test
+export DATASET_ID=test
+export DIRECTION="deA-enA"
+export LINE_NO_START=0
+export LINE_NO_END=10
+python fetch_dataset_s2s.py

main_s2t.sh

@@ -0,0 +1,60 @@
+######################
+# enA-jpn: 1_468_292 #
+######################
+# test
+export DATASET_ID=test
+export DIRECTION="enA-jaA"
+export LINE_NO_START=0
+export LINE_NO_END=10
+python download_audio.py
+
+
+# DOWNLOAD AUDIO
+for i in $(seq 91 100);
+do
+  export N_POOL=15
+  export DATASET_ID=${i}
+  export DIRECTION="enA-jpn"
+  export LINE_NO_START=$(((DATASET_ID-1) * 2500))
+  export LINE_NO_END=$((DATASET_ID * 2500))
+  echo ${LINE_NO_START}
+  python download_audio.py
+done
+
+# download text
+git clone https://github.com/kpu/preprocess
+cd preprocess
+git checkout wet
+git submodule update --init --recursive
+mkdir build
+cd build
+cmake ..
+make -j4
+alias wet_lines="${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 ./
+python format_text.py
+mv text.enA-jpn.json ../
+cd ../
+
+
+########
+# 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')"
+