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A curated ~10,000-clip sample of social talking-head video with timestamped transcripts. Shofo has aggregated billions of videos into a searchable index to curate custom datasets at scale. Fill out the following for access:
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Shofo Talking Head Dataset (English)
A curated dataset of ~10,000 talking-head videos (~186 hours, mean ~67s/clip), filtered for clean single-speaker framing and paired with time-aligned transcripts. Built and released by Shofo.
This dataset is short-form social video, designed to support modern avatar, lip-sync, dubbing, and TTS work. Every clip is curated by a multi-stage pipeline (face/framing analysis, on-screen-text detection, object-occlusion detection, voice/face matching, language detection) to provide a curated dataset rather than a raw dump.
What makes a clip eligible
Each clip in this release satisfies all of the following (derived by Shofo's curation pipeline):
- Single, centered, persistently-visible face (face present ≥95% of frames, low framing jitter, no multi-face).
- On-camera speech: the speaker's voice matches the on-screen face (not dubbed/voiceover).
- Audio-visual sync verified: lip motion correlates with the audio, checked with a SyncNet-based AV-sync model plus a sound-attribution pass that flags clips mimed to a borrowed sound. Lip-syncs, dubs, and mimed clips are removed.
- Active speaking (detected mouth motion).
- Face not occluded (screened for objects blocking the face; occlusion of the body or by props is not fully filtered).
- English (dual-detector language ID, high confidence).
- Duration 10s to 300s.
The ~10,000 clips are selected by a composite quality score together with the curation gates above.
Dataset structure
metadata.parquet # one row per clip (schema below)
videos/{ab}/{video_id}.mp4 # H.264/MP4, sharded by first 2 chars of id [if files hosted]
Fields
| field | description |
|---|---|
video |
the clip itself (decoded Video feature, auto-generated) |
video_id |
TikTok numeric video id (stable reference) |
tiktok_url |
handle-less source link https://www.tiktok.com/@i/video/{id} |
duration_ms |
clip duration (ms) |
resolution, width, height |
frame dimensions |
fps, codec, bitrate, has_audio |
technical metadata (ffprobe) |
language |
detected spoken language (en) |
has_music |
music detected in audio |
transcript |
time-aligned, segment-level WEBVTT transcript with punctuation (all clips) |
Every clip is selected by Shofo's multi-signal curation pipeline (face/framing, on-screen-text, occlusion, voice/face matching, language); see What makes a clip eligible above.
Transcripts cover all clips and were produced with NVIDIA Canary-Qwen-2.5B.
Usage
from datasets import load_dataset
# Auto-detected as a videofolder: each row has a decoded `video` column
# plus all metadata fields (scores, transcript, technical info).
ds = load_dataset("Shofo/shofo-talking-head-en", split="train")
row = ds[0]
print(row["video_id"], row["resolution"], row["duration_ms"])
video = row["video"] # decoded video (Video feature)
Each row also carries file_name if you prefer to fetch the raw mp4 directly via huggingface_hub.hf_hub_download.
Known limitations
- Resolution is modest. Clips are vertical social video, 88% 576×1024 (SD) and 9% 720×1280; curation and composition quality is high but native resolution is not HD. Face crops are typically 300 to 400px tall. (All clips are H.264/MP4, portrait, with audio, bitrate 400 kbps or higher.)
- A small number of lip-syncs may remain. Clips were screened for audio-visual sync (SyncNet-based scoring plus a sound-attribution check) and flagged lip-syncs, dubs, and mimed clips were removed, but a low single-digit percentage of hard cases can slip through. Screen for it if your task is sync-sensitive.
- Some fine-grained issues remain. Composition signals can't catch everything (e.g. green-screen compositing).
About Shofo & more data
This is a curated sample. Shofo has aggregated billions of social videos into a searchable index with rich derived metadata (captions, embeddings, quality/occlusion/text scores, transcripts), and builds custom curated datasets at scale. Interested in larger or task-specific data? Reach us at founders@shofo.ai / https://shofo.ai
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