Datasets:

HJOK
/

openetd-metadata

license: cc-by-4.0
language: en
task_categories:
  - audio-classification
tags:
  - end-turn-detection
  - turn-taking
  - spoken-dialogue
  - conversation
pretty_name: OpenETD Metadata
size_categories:
  - 100K<n<1M

OpenETD metadata

Train / dev / test split CSVs for the OpenETD dataset released with the ACL 2026 Findings paper Speculative End-Turn Detector for Efficient Speech Chatbot Assistant (arXiv:2503.23439).

Code: https://github.com/HJ-Ok/OpenETD

Split sizes

Split	Real files	Real hours	Synthetic files	Synthetic hours
train	6,290	117.2	96,773	116.8
dev	899	16.2	12,840	15.8
test	1,798	32.4	12,868	15.7

Columns

Column	Description
`file_path`	Relative path to the audio file (resolve locally).
`pause_times`	Interval list `(start, end), ...` of within-speaker pauses (seconds).
`gap_times`	Interval list `(start, end), ...` of between-speaker gaps (seconds).
`contains_pause`	Boolean, whether the file contains any pause.
`contains_gap`	Boolean, whether the file contains any gap.
`label`	Type of the final silence (`Pause` or `Gap`); used for the binary task.
`platform`	(Real only) `buckeye` or `youtube`.
`kfold`	(Synthetic only) k-fold assignment used for pause/gap label generation.

Audio files

Audio is NOT included in this repository — we redistribute only the annotations and split assignments. To obtain the audio:

Buckeye audio: obtain from the Buckeye Corpus maintainers under their Academic License, then place files under data/real/audio/buckeye_full/.
YouTube audio: download with the helper script in OpenETD repository (scripts/prepare_data.sh).
Synthetic audio: regenerate on your own Google Cloud account using data/synthetic_pipeline/generate.py in the OpenETD repository.

Quick start

from datasets import load_dataset
ds = load_dataset("HJOK/openetd-metadata", data_files={
    "real_train":  "real/train.csv",
    "real_valid":  "real/valid.csv",
    "real_test":   "real/test.csv",
    "syn_train":   "synthetic/train.csv",
    "syn_valid":   "synthetic/valid.csv",
    "syn_test":    "synthetic/test.csv",
})
print(ds["real_test"][0])

License

Annotations (this repository): CC BY 4.0
Code in the OpenETD GitHub repository: MIT
External audio sources retain their original licenses (see DATA_LICENSES.md in the GitHub repo).

Citation

@inproceedings{ok2026speculativeetd,
  title     = {Speculative End-Turn Detector for Efficient Speech Chatbot Assistant},
  author    = {Ok, Hyunjong and Yoo, Suho and Lee, Jaeho},
  booktitle = {Findings of the Association for Computational Linguistics: ACL 2026},
  year      = {2026},
  url       = {https://arxiv.org/abs/2503.23439}
}