| """Rebuild audio for the sea-asr label datasets from the source videos. The datasets ship no audio. |
| |
| Pattern from PleIAs, YouTube-Commons (https://huggingface.co/datasets/PleIAs/YouTube-Commons): publish transcripts |
| and source ids; users fetch the audio themselves from the original Creative Commons videos. |
| |
| pip install pyarrow soundfile numpy yt-dlp # and ffmpeg on PATH |
| python fetch_audio.py --data data/ --out audio/ [--limit-videos 10] |
| |
| Writes <out>/<segment_id>.flac (16 kHz mono) and <out>/manifest.jsonl ({segment_id, audio, text, start, end}). |
| Each video stays under its creator's CC-BY licence: keep the attribution (ATTRIBUTION.tsv) with any copy you make. |
| Videos can be deleted or changed upstream; segments whose source is gone are skipped and counted. |
| """ |
|
|
| import argparse |
| import glob |
| import json |
| import os |
| import subprocess |
| import tempfile |
|
|
| import numpy as np |
| import pyarrow.parquet as pq |
| import soundfile as sf |
|
|
| SR = 16000 |
|
|
|
|
| def fetch_video(video_id: str, tmp: str) -> np.ndarray | None: |
| """Best audio of one YouTube video as 16 kHz mono float32, or None if unavailable.""" |
| path = os.path.join(tmp, video_id) |
| r = subprocess.run(["yt-dlp", "-q", "--no-warnings", "-f", "bestaudio", "-o", path + ".%(ext)s", |
| f"https://www.youtube.com/watch?v={video_id}"], capture_output=True) |
| files = glob.glob(path + ".*") |
| if r.returncode != 0 or not files: |
| return None |
| raw = subprocess.run(["ffmpeg", "-nostdin", "-loglevel", "error", "-i", files[0], "-ac", "1", "-ar", str(SR), |
| "-f", "f32le", "-"], capture_output=True).stdout |
| for f in files: |
| os.remove(f) |
| return np.frombuffer(raw, dtype=np.float32) if raw else None |
|
|
|
|
| def main(): |
| ap = argparse.ArgumentParser() |
| ap.add_argument("--data", required=True, help="folder with the dataset's data-*.parquet files") |
| ap.add_argument("--out", required=True) |
| ap.add_argument("--limit-videos", type=int, default=0) |
| a = ap.parse_args() |
| os.makedirs(a.out, exist_ok=True) |
| cols = ["source_id", "segment_id", "start", "end", "text_norm"] |
| rows = [r for f in sorted(glob.glob(os.path.join(a.data, "*.parquet"))) for r in pq.read_table(f, columns=cols).to_pylist()] |
| by_vid: dict[str, list[dict]] = {} |
| for r in rows: |
| by_vid.setdefault(r["source_id"], []).append(r) |
| vids = sorted(by_vid)[: a.limit_videos or None] |
| done = gone = 0 |
| with tempfile.TemporaryDirectory() as tmp, open(os.path.join(a.out, "manifest.jsonl"), "a", encoding="utf-8") as man: |
| for vid in vids: |
| wav = fetch_video(vid, tmp) |
| if wav is None: |
| gone += len(by_vid[vid]) |
| continue |
| for r in by_vid[vid]: |
| seg = wav[int(r["start"] * SR): int(r["end"] * SR)] |
| if len(seg) < SR // 2: |
| gone += 1 |
| continue |
| path = os.path.join(a.out, r["segment_id"] + ".flac") |
| sf.write(path, seg, SR) |
| man.write(json.dumps({"segment_id": r["segment_id"], "audio": path, "text": r["text_norm"], |
| "start": r["start"], "end": r["end"]}, ensure_ascii=False) + "\n") |
| done += 1 |
| print(f"segments written {done}, skipped (video gone or too short) {gone}") |
|
|
|
|
| if __name__ == "__main__": |
| main() |
|
|
