Sinoosoida/SpeachRus

MyBook Podcasts (unlabeled)

Unlabeled Russian-language podcast episodes scraped from mybook.ru, packaged as Parquet shards with audio bytes embedded.

Each row of the dataset contains:

• audio — the podcast episode (MP3), decoded on-the-fly via the Audio feature.
• ~30 flat scalar metadata columns: id, name, slug, lang, duration_sec, audio_bytes, rating, rating_votes, rating_scores, read_count, reviews_count, citations_count, main_author_*, main_actor_*, publisher_name, genres_names, tags_csv, series_name, subscription_id, written_dt, updated_at, share_url, default_cover_path, preview_audio_url, annotation_plain, annotation_html.
• raw_metadata_json — the full original page-JSON from mybook (89 fields with all nested structures: counters, niche category info, full author/ actor records, tag covers, etc) serialized as a string.

Loading examples

from datasets import load_dataset

# stream the whole thing
ds = load_dataset("USERNAME/mybook-podcasts", split="train", streaming=True)
for ex in ds.take(3):
    print(ex["name"], ex["duration_sec"], ex["rating"])
    audio = ex["audio"]  # AudioDecoder

# metadata-only: skip downloading audio bytes
ds = load_dataset(
    "USERNAME/mybook-podcasts", split="train", streaming=True,
    columns=["id", "name", "duration_sec", "rating", "genres_names"],
)

# filter by metadata
ds = load_dataset(
    "USERNAME/mybook-podcasts", split="train", streaming=True,
    filters=[("duration_sec", ">", 3600)],  # podcasts longer than 1 hour
)

This dataset is built incrementally over time.