Update README.md

README.md

@@ -34,4 +34,124 @@ configs:
   data_files:
   - split: train
     path: data/train-*
+license: cc-by-4.0
+language:
+- en
+- fr
+- es
+- pt
+- de
+- ru
+- nl
+- tr
+- it
+pretty_name: YouTube Commons Descriptions
 ---
+
+# YouTube Commons Descriptions and Language Detection
+This dataset is based on [YouTube Commons](https://huggingface.co/datasets/PleIAs/YouTube-Commons), a valuable open dataset:
+> YouTube-Commons is a collection of audio transcripts of 2,063,066 videos shared on YouTube under a CC BY 4.0 license.
+>
+> **Content**
+>
+> The collection comprises 22,709,724 original and automatically translated transcripts from 3,156,703 videos (721,136 individual channels).
+
+Unfortunately I have found that the detection of the original language, at least for Dutch, has room for improvement.
+Others have observed ([1](https://huggingface.co/datasets/PleIAs/YouTube-Commons/discussions/9), [2](https://huggingface.co/datasets/PleIAs/YouTube-Commons/discussions/12)) similar issues.
+Therefore this dataset adds the video **title** and **description** to YouTube Commons and performs **language detection** on those.
+
+# YouTube Commons
+There are [problems](https://huggingface.co/datasets/PleIAs/YouTube-Commons/discussions/10) with loading YouTube Commons with Hugging Face Datasets.
+To alleviate those, I took the source parquet-files and reuploaded a fixed version to HuggingFace: [Rijgersberg/YouTube-Commons](https://huggingface.co/datasets/Rijgersberg/YouTube-Commons).
+This reupload is the basis for YouTube Commons Descriptions.
+
+## Acquisition
+The titles and descriptions are downloaded from YouTube with the help of [yt-dlp](https://github.com/yt-dlp/yt-dlp).
+Some videos are missing compared to YouTube Commons, for one of the following reasons:
+
+- Some videos are no longer available on YouTube, either taken down by the uploader or by YouTube.
+- Some videos are only visible to logged in users.
+- (rarely) Anti-bot measures by YouTube prevented download.
+
+The download took about two weeks.
+
+Code:
+```python
+import json
+from concurrent.futures import ProcessPoolExecutor, as_completed
+from pathlib import Path
+
+from datasets import load_dataset
+from tqdm import tqdm
+from yt_dlp import YoutubeDL
+
+output_dir = Path('/path/to/output/dir/')
+
+
+def get_info(video_id, output_dir):
+    write_folder = output_dir / video_id[:2]
+    write_filepath = write_folder / f'{video_id}.json'
+    if write_filepath.exists():
+        return video_id, True
+
+    with YoutubeDL({'quiet': True, 'skip_download': True}) as ydl:
+        try:
+            info = ydl.extract_info(f'https://www.youtube.com/watch?v={video_id}', download=False)
+
+            title = info.get('title', '')
+            description = info.get('description', '')
+
+            # Write the title and description to a text file
+            write_folder.mkdir(exist_ok=True, parents=True)
+            with open(write_filepath, 'w', encoding='utf-8') as f:
+                json.dump({'id': video_id,
+                           'title': title,
+                           'description': description}, f)
+        except Exception as e:
+            print(video_id, e)
+            return video_id, False
+    return video_id, True
+
+def main():
+    video_ids = []
+    for filepath in tqdm(sorted(Path('/path/to/YouTubeCommons/files').rglob('*.parquet'))):
+        try:  # I was having trouble loading the original dataset, so this lets me get what I can
+            dataset = load_dataset("parquet",
+                                   data_files={'train': str(filepath)})
+            video_ids.extend(dataset['train']['video_id'])
+        except Exception as e:
+            print(filepath, e)
+            continue
+    video_ids = set(video_ids)
+
+    with ProcessPoolExecutor(max_workers=10) as executor:
+        futures = {executor.submit(get_info, video_id, output_dir): video_id
+                   for video_id in video_ids}
+
+        for future in tqdm(as_completed(futures), total=len(futures), desc="Downloading video info"):
+            video_id = futures[future]
+            try:
+                _, success = future.result()
+                if not success:
+                    print(f"Failed to process: {video_id}")
+            except Exception as e:
+                print(f"Error occurred for {video_id}: {e}")
+
+if __name__ == "__main__":
+    main()
+```
+
+
+## Language detection
+The `language` and `confidence` columns were added by running [LangID](https://github.com/saffsd/langid.py) on the title and description.
+So note: the detection was _not_ performed on the audio of the video.
+
+The equivalent detection code:
+```python
+from langid.langid import LanguageIdentifier, model
+
+lang_id = LanguageIdentifier.from_modelstring(model, norm_probs=True)
+
+lang, conf = lang_id.classify(title + '\n\n' + description)
+```
+