new ui

download_audio.py

@@ -136,8 +136,10 @@ def process_dataset():
             if not flag:
                 print(f"failed:\n{g['url']}")
     else:
-        with Pool(n_pool) as pool:
-            pool.map(get_audio, tqdm(inputs, total=len(inputs)))
+        for i in range(0, len(inputs), n_pool):
+            batch_inputs = inputs[i: min(len(inputs), i + n_pool)]
+            with Pool(n_pool) as pool:
+                pool.map(get_audio, tqdm(batch_inputs, total=len(batch_inputs)))
 
 
     def loader(feature: str) -> Dict:

filter_audio.py

@@ -1,51 +0,0 @@
-import json
-import os
-from os.path import join as p_join
-from tqdm import tqdm
-from typing import Dict
-from glob import glob
-import soundfile as sf
-
-from datasets import Audio
-
-# dataset config
-direction = os.getenv("DIRECTION", "enA-jpn")
-direction_speech = os.getenv("DIRECTION_SPEECH", "enA")
-cache_dir_audio = p_join("download", "audio", direction)
-cache_dir_feature = p_join("download", "feature", direction)
-cache_dir_audio_fixed = p_join("download", "audio_fixed", direction, direction_speech)
-os.makedirs(cache_dir_feature, exist_ok=True)
-os.makedirs(cache_dir_audio, exist_ok=True)
-os.makedirs(cache_dir_audio_fixed, exist_ok=True)
-line_no_start = int(os.getenv("LINE_NO_START", 0))
-line_no_end = int(os.getenv("LINE_NO_END", 100))
-
-
-def loader(feature: str) -> Dict:
-    with open(feature) as f_reader:
-        return json.load(f_reader)
-
-
-# feature dictionary
-files = {
-    int(os.path.basename(i).replace(".json", "")): i for i in glob(p_join(cache_dir_feature, "*.json"))
-}
-# feature files
-files_list = [k for k in files.keys() if line_no_start <= k <= line_no_end]
-fixed_audio_list = [int(os.path.basename(i).replace(".mp3", "")) for i in glob(p_join(cache_dir_audio_fixed, "*"))]
-# remove broken audio files
-audio_loader = Audio()
-index_list = [i for i in list(range(line_no_start, line_no_end)) if i in files_list and i not in fixed_audio_list]
-print(f"filtering {len(index_list)} files....")
-for i in tqdm(index_list):
-    features = loader(files[i])
-    audio_file = features[f"{direction_speech}.path"]
-    start, end = features[f"{direction_speech}.duration_start"], features[f"{direction_speech}.duration_end"]
-    if os.path.exists(audio_file):
-        try:
-            wav = audio_loader.decode_example({"path": audio_file, "bytes": None})
-            if start < end < len(wav["array"]):
-                sf.write(p_join(cache_dir_audio_fixed, f"{i}.mp3"), wav["array"][start:end], wav["sampling_rate"])
-        except Exception as e:
-            print(e)
-            os.remove(audio_file)

main.sh

@@ -32,14 +32,20 @@ export LINE_NO_END=$((DATASET_ID * 5000))
 python download_audio.py
 
 
-export DATASET_ID=12
+export DATASET_ID=11
 export DIRECTION="enA-jaA"
 export LINE_NO_START=$(((DATASET_ID-1) * 5000))
 export LINE_NO_END=$((DATASET_ID * 5000))
 python download_audio.py
 
+export DATASET_ID=13
+export DIRECTION="enA-jaA"
+export LINE_NO_START=$(((DATASET_ID-1) * 5000))
+export LINE_NO_END=$((DATASET_ID * 5000))
+python download_audio.py
 
-export DATASET_ID=14
+
+export DATASET_ID=15
 export DIRECTION="enA-jaA"
 export LINE_NO_START=$(((DATASET_ID-1) * 5000))
 export LINE_NO_END=$((DATASET_ID * 5000))
@@ -72,8 +78,6 @@ export LINE_NO_START=$(((DATASET_ID-1) * 5000))
 export LINE_NO_END=$((DATASET_ID * 5000))
 python download_audio.py
 
-
-
 export DATASET_ID=22
 export DIRECTION="enA-jaA"
 export LINE_NO_START=$(((DATASET_ID-1) * 5000))

push_s2s_translation.py

@@ -1,115 +0,0 @@
-import json
-import os
-import time
-from os.path import join as p_join
-from tqdm import tqdm
-from typing import Dict
-from glob import glob
-
-from soundfile import LibsndfileError
-from datasets import Dataset, Audio, DatasetDict
-
-# dataset config
-direction = os.getenv("DIRECTION", "enA-jaA")
-sides = {i: n for n, i in enumerate(sorted(direction.split("-")), 1)}
-sides_rev = {v: k for k, v in sides.items()}
-cache_dir_audio = p_join("download", "audio", direction)
-cache_dir_feature = p_join("download", "feature", direction)
-os.makedirs(cache_dir_audio, exist_ok=True)
-os.makedirs(cache_dir_feature, exist_ok=True)
-line_no_start = int(os.getenv("LINE_NO_START", 0))
-line_no_end = int(os.getenv("LINE_NO_END", 10000))
-dataset_id = int(os.getenv("DATASET_ID", 0))
-hf_org = "kotoba-tech"
-hf_dataset = f"seamless-align-{direction}"
-
-
-def loader(feature: str) -> Dict:
-    with open(feature) as f:
-        return json.load(f)
-
-
-# create a dataset instance
-
-files = {
-    int(os.path.basename(i).replace(".json", "")): i for i in glob(p_join(cache_dir_feature, "*.json"))
-}
-file_ids = [i for i in range(line_no_start, line_no_end) if i in files]
-features = [loader(files[i]) for i in file_ids]
-print(f"features: {len(features)}")
-features = [i for i in features if os.path.exists(i[f"{sides_rev[1]}.path"]) and os.path.exists(i[f"{sides_rev[2]}.path"])]
-print(f"features (filtered): {len(features)}")
-data_dict = {
-    f"{sides_rev[1]}.audio": [i.pop(f"{sides_rev[1]}.path") for i in features],
-    f"{sides_rev[2]}.audio": [i.pop(f"{sides_rev[2]}.path") for i in features]
-}
-keys = features[0].keys()
-data_dict.update(
-    {k: [i[k] for i in features] for k in keys}
-)
-audio_dataset = Dataset.from_dict(data_dict)
-audio_dataset = audio_dataset.cast_column(f"{sides_rev[1]}.audio", Audio())
-audio_dataset = audio_dataset.cast_column(f"{sides_rev[2]}.audio", Audio())
-
-# remove instances with broken audio files
-broken_files = []
-for i in tqdm(range(len(audio_dataset))):
-    try:
-        a = audio_dataset[i]
-        flag = True
-        for side_id in sides_rev.keys():
-            start = a[f"{sides_rev[side_id]}.duration_start"]
-            end = a[f"{sides_rev[side_id]}.duration_end"]
-            array = a[f"{sides_rev[side_id]}.audio"]["array"]
-            flag = 0 < start < end < len(array)
-        if not flag:
-            broken_files.append(i)
-    except LibsndfileError:
-        broken_files.append(i)
-        continue
-print(f"features (removed broken audio): {len(audio_dataset) - len(broken_files)}")
-if len(broken_files) > 0:
-    print(f"found {len(broken_files)} broken files:")
-    flag = input("delete the broken files? (y/n): ")
-    if flag == "y":
-        # remove broken files
-        for i in broken_files:
-            if os.path.exists(files[file_ids[i]]):
-                os.remove(files[file_ids[i]])
-            for side_id in sides_rev.keys():
-                if os.path.exists(data_dict[f"{sides_rev[side_id]}.audio"][i]):
-                    os.remove(data_dict[f"{sides_rev[side_id]}.audio"][i])
-valid_data_id = [i for i in range(len(audio_dataset)) if i not in broken_files]
-audio_dataset_valid = audio_dataset.select(valid_data_id)
-
-
-# trim the audio according to the duration
-def clip_audio(batch):
-    for side_id in sides_rev.keys():
-        start = batch[f"{sides_rev[side_id]}.duration_start"]
-        end = batch[f"{sides_rev[side_id]}.duration_end"]
-        audio = batch[f"{sides_rev[side_id]}.audio"]
-        batch[f"{sides_rev[side_id]}.audio"] = [
-            {"array": a["array"][s:e], "sampling_rate": a["sampling_rate"]}
-            for a, s, e in zip(audio, start, end)
-        ]
-    return batch
-
-
-audio_dataset_valid = audio_dataset_valid.map(
-    function=clip_audio,
-    batched=True,
-    batch_size=128,
-    num_proc=1,
-    desc="clipping audio based on the duration:"
-)
-
-dataset_to_push = DatasetDict({"train": audio_dataset_valid})
-repo_name = f"{hf_org}/{hf_dataset}"
-while True:
-    try:
-        dataset_to_push.push_to_hub(repo_name, config_name=f"subset_{dataset_id}")
-        break
-    except Exception:
-        print(f"FAILED: push_to_hub on {repo_name} failed. wait 60 sec and retry soon...")
-        time.sleep(60)

push_s2t_translation.py

@@ -1,94 +0,0 @@
-import json
-import os
-import time
-from os.path import join as p_join
-from tqdm import tqdm
-from typing import Dict
-from glob import glob
-
-from soundfile import LibsndfileError
-from datasets import Dataset, Audio, DatasetDict
-
-# dataset config
-direction_speech = os.getenv("DIRECTION_SPEECH", "enA")
-direction_text = os.getenv("DIRECTION_TEXT", "jpn")
-direction = f"{direction_speech}-{direction_text}"
-with open(f"text.{direction}.json") as f:
-    line2text = json.load(f)
-cache_dir_audio = p_join("download", "audio", direction)
-cache_dir_feature = p_join("download", "feature", direction)
-os.makedirs(cache_dir_audio, exist_ok=True)
-os.makedirs(cache_dir_feature, exist_ok=True)
-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 = "kotoba-tech"
-hf_dataset = f"seamless-align-{direction}"
-
-
-def loader(feature: str) -> Dict:
-    with open(feature) as f:
-        return json.load(f)
-
-
-# create a dataset instance
-
-files = {
-    int(os.path.basename(i).replace(".json", "")): i for i in glob(p_join(cache_dir_feature, "*.json"))
-}
-
-
-def delete_audio(target_audio_file):
-    if os.path.exists(target_audio_file):
-        os.remove(target_audio_file)
-    line_no = os.path.basename(target_audio_file).split(".")[0]
-    try:
-        feature_file = files[int(line_no)]
-        if os.path.exists(feature_file):
-            os.remove(feature_file)
-    except Exception as e:
-        print(e)
-
-
-# remove broken audio files
-print("filtering....")
-features = []
-audio_loader = Audio()
-for i in tqdm(list(range(line_no_start, line_no_end))):
-    if i not in files:
-        continue
-    i = loader(files[i])
-    i[f"{direction_text}.text"] = line2text[str(i["line_no"])]
-    audio_file = i.pop(f"{direction_speech}.path")
-    start, end = i[f"{direction_speech}.duration_start"], i[f"{direction_speech}.duration_end"]
-    if os.path.exists(audio_file):
-        try:
-            wav = audio_loader.decode_example({"path": audio_file, "bytes": None})
-            if start < end < len(wav["array"]):
-                wav["array"] = wav["array"][start:end]
-                i[f"{direction_speech}.audio"] = wav
-                features.append(i)
-            else:
-                delete_audio(audio_file)
-        except Exception as e:
-            print(e)
-            delete_audio(audio_file)
-
-
-print(f"features (filtered): {len(features)}")
-keys = features[0].keys()
-data_dict = {k: [i[k] for i in features] for k in keys}
-audio_dataset = Dataset.from_dict(data_dict)
-audio_dataset = audio_dataset.cast_column(f"{direction_speech}.audio", Audio())
-dataset_to_push = DatasetDict({"train": audio_dataset})
-repo_name = f"{hf_org}/{hf_dataset}"
-while True:
-    try:
-        dataset_to_push.push_to_hub(repo_name, config_name=f"subset_{dataset_id}")
-        break
-    except Exception:
-        print(f"FAILED: push_to_hub on {repo_name} failed. wait 60 sec and retry soon...")
-        time.sleep(60)
-os.makedirs("log", exist_ok=True)
-with open(f"log/pushed.line_no.{dataset_id}.json", "w") as f:
-    json.dump(data_dict["line_no"], f)