TalkVid: A Large-Scale Diversified Dataset for Audio-Driven Talking Head Synthesis
Paper • 2508.13618 • Published • 20
Datasets:
Dataset Viewer
The dataset viewer is not available for this split.
Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code: StreamingRowsError
Exception: CastError
Message: Couldn't cast
id: string
height: int64
width: int64
fps: double
start-time: double
start-frame: int64
end-time: double
end-frame: int64
durations: string
info: struct<Person ID: string, Ethnicity: string, Age Group: string, Gender: string, Video Link: string, (... 41 chars omitted)
child 0, Person ID: string
child 1, Ethnicity: string
child 2, Age Group: string
child 3, Gender: string
child 4, Video Link: string
child 5, Language: string
child 6, Video Category: string
description: string
dover_scores: double
cotracker_ratio: double
head_detail: struct<scores: struct<avg_movement: double, min_movement: double, avg_rotation: double, min_rotation (... 160 chars omitted)
child 0, scores: struct<avg_movement: double, min_movement: double, avg_rotation: double, min_rotation: double, avg_c (... 144 chars omitted)
child 0, avg_movement: double
child 1, min_movement: double
child 2, avg_rotation: double
child 3, min_rotation: double
child 4, avg_completeness: double
child 5, min_completeness: double
child 6, avg_resolution: double
child 7, min_resolution: double
child 8, avg_orientation: double
child 9, min_orientation: double
sample_index: int64
use_id: string
actual_source_start: double
actual_source_end: double
video_file: string
audio_file: string
timing_method: string
max_frame_timestamp_error_seconds: double
first_frame_mean_luma: double
audio_validation: string
offset_ms: double
correlation: double
mode: string
global_indices_preserved: bool
runnable_clips: int64
source_videos: int64
assigned_clips: int64
assignment_id: string
to
{'assignment_id': Value('string'), 'assigned_clips': Value('int64'), 'runnable_clips': Value('int64'), 'source_videos': Value('int64'), 'global_indices_preserved': Value('bool'), 'mode': Value('string')}
because column names don't match
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/utils.py", line 147, in get_rows_or_raise
return get_rows(
dataset=dataset,
...<4 lines>...
column_names=column_names,
)
File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
return func(*args, **kwargs)
File "/src/services/worker/src/worker/utils.py", line 127, in get_rows
rows_plus_one = list(itertools.islice(safe_iter(ds, dataset=dataset), rows_max_number + 1))
File "/src/services/worker/src/worker/utils.py", line 483, in safe_iter
yield from ds.decode(False) if ds.features else ds
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2951, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2461, in __iter__
for key, pa_table in self._iter_arrow():
~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2486, in _iter_arrow
for key, pa_table in self.ex_iterable._iter_arrow():
~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 547, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 430, in _iter_arrow
for key, pa_table in self.generate_tables_fn(**gen_kwags):
~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 343, in _generate_tables
self._cast_table(pa_table, json_field_paths=json_field_paths),
~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 132, in _cast_table
pa_table = table_cast(pa_table, self.info.features.arrow_schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2378, in table_cast
return cast_table_to_schema(table, schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2306, in cast_table_to_schema
raise CastError(
...<3 lines>...
)
datasets.table.CastError: Couldn't cast
id: string
height: int64
width: int64
fps: double
start-time: double
start-frame: int64
end-time: double
end-frame: int64
durations: string
info: struct<Person ID: string, Ethnicity: string, Age Group: string, Gender: string, Video Link: string, (... 41 chars omitted)
child 0, Person ID: string
child 1, Ethnicity: string
child 2, Age Group: string
child 3, Gender: string
child 4, Video Link: string
child 5, Language: string
child 6, Video Category: string
description: string
dover_scores: double
cotracker_ratio: double
head_detail: struct<scores: struct<avg_movement: double, min_movement: double, avg_rotation: double, min_rotation (... 160 chars omitted)
child 0, scores: struct<avg_movement: double, min_movement: double, avg_rotation: double, min_rotation: double, avg_c (... 144 chars omitted)
child 0, avg_movement: double
child 1, min_movement: double
child 2, avg_rotation: double
child 3, min_rotation: double
child 4, avg_completeness: double
child 5, min_completeness: double
child 6, avg_resolution: double
child 7, min_resolution: double
child 8, avg_orientation: double
child 9, min_orientation: double
sample_index: int64
use_id: string
actual_source_start: double
actual_source_end: double
video_file: string
audio_file: string
timing_method: string
max_frame_timestamp_error_seconds: double
first_frame_mean_luma: double
audio_validation: string
offset_ms: double
correlation: double
mode: string
global_indices_preserved: bool
runnable_clips: int64
source_videos: int64
assigned_clips: int64
assignment_id: string
to
{'assignment_id': Value('string'), 'assigned_clips': Value('int64'), 'runnable_clips': Value('int64'), 'source_videos': Value('int64'), 'global_indices_preserved': Value('bool'), 'mode': Value('string')}
because column names don't matchNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
TalkVid processed video clips
This repository is a processed mirror/subset in progress of FreedomIntelligence/TalkVid, not a new original dataset. Credit belongs to the TalkVid authors. See the official project and paper. Dataset use is subject to CC BY-NC 4.0 and the original project's non-commercial research terms.
Files and progress
Files are uploaded incrementally. The original metadata is divided into five logical batches of approximately 20% of records each. A batch directory existing does not mean it is complete. A source can be unavailable; errors must not be interpreted as successful samples. Only uploaded shards are available here.
data/batch-01/throughdata/batch-05/: TAR shards, normally up to 1,000 samples or about 4 GiB of media per shard (a single large sample may exceed this target).metadata/batch-XX/*.jsonl: the corresponding sample annotations.- Each TAR contains
<Person ID>_<original id>.mp4,<Person ID>_<original id>.m4a, and<Person ID>_<original id>.json. The index is zero-based in the pinned metadata order.
Processing and synchronization
Videos are downloaded from the YouTube URLs in the original annotations. Source resolution is retained. Video is encoded as H.264 CRF 18; audio as AAC 128 kbps. Both streams are cut on one shared source time axis. Start and end cuts are snapped forward to actual source video frame boundaries, and the same origin is subtracted from audio and video. actual_source_start and actual_source_end record the effective cuts; original time/frame annotations remain in the JSON. No independent video time shift is applied.
Checks require a non-black first decoded frame, near-zero stream start times, source-matching video frame times, and decoded audio alignment with the same source interval (within 1 ms for non-silent clips). Independent M4A audio matches the MP4 audio. These checks preserve the source's timing; they do not establish that every original source has perfect perceptual lip synchronization. Problematic clips are recorded locally for review instead of silently treated as successful.
Each shard is verified against its immutable Hub commit and SHA-256 before its local copy is removed. Full-resolution media can be large; this repository is a work in progress and may pause due to source availability or storage quotas.
use_id in each JSON is copied from the original info["Person ID"]. Example: 597_videovideoTr6MMsoWAog-scene1-scene1.mp4. A source ending may produce a smaller shard; the limit is a maximum, not a fixed shard size.
Scheduling prioritizes Person ID groups, but idle workers may start later people while slow jobs for an earlier person continue. At most six source jobs run concurrently, with at most two ffmpeg/ffprobe processes at a time to bound CPU and memory use. Per-source failures remain explicitly incomplete; upload verification, disk or proxy failures pause the run. Logical batch paths retain their original index-based partition and may populate out of order.
Source frame timestamps are inspected only around each target interval using bounded local scans, rather than decoding each full source in advance. Original source timestamps and the shared audio/video origin remain unchanged.
- Downloads last month
- 12,400