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---
dataset_info:
features:
- name: audio
dtype: audio
- name: timestamps_start
sequence: float64
- name: timestamps_end
sequence: float64
- name: speakers
sequence: string
splits:
- name: dev
num_bytes: 2338411143
num_examples: 216
- name: test
num_bytes: 5015872396
num_examples: 232
download_size: 7296384603
dataset_size: 7354283539
configs:
- config_name: default
data_files:
- split: dev
path: data/dev-*
- split: test
path: data/test-*
tags:
- speaker diarization
- voice activity detection
license: cc-by-4.0
language:
- en
---
# Dataset Card for the Voxconverse dataset
VoxConverse is an audio-visual diarisation dataset consisting of multispeaker clips of human speech, extracted from YouTube videos. Updates and additional information about the dataset can be found on the [dataset website](https://www.robots.ox.ac.uk/~vgg/data/voxconverse/index.html).
Note: This dataset has been preprocessed using [diarizers](https://github.com/huggingface/diarizers/tree/main/datasets). It makes the dataset compatible with diarizers to fine-tune [pyannote](https://huggingface.co/pyannote/segmentation-3.0) segmentation models.
# Example Usage
```
from datasets import load_dataset
ds = load_dataset("diarizers-community/voxconverse")
print(ds)
```
gives:
```
DatasetDict({
train: Dataset({
features: ['audio', 'timestamps_start', 'timestamps_end', 'speakers'],
num_rows: 136
})
validation: Dataset({
features: ['audio', 'timestamps_start', 'timestamps_end', 'speakers'],
num_rows: 18
})
test: Dataset({
features: ['audio', 'timestamps_start', 'timestamps_end', 'speakers'],
num_rows: 16
})
})
```
# Dataset source
- Homepage: https://www.robots.ox.ac.uk/~vgg/data/voxconverse/
- Repository: https://github.com/joonson/voxconverse?tab=readme-ov-file
- Preprocessed using [diarizers](https://github.com/kamilakesbi/diarizers/tree/main/datasets)
# Citation
```
@article{chung2020spot,
title={Spot the conversation: speaker diarisation in the wild},
author={Chung, Joon Son and Huh, Jaesung and Nagrani, Arsha and Afouras, Triantafyllos and Zisserman, Andrew},
booktitle={Interspeech},
year={2020}
}
```
# Contribution
Thanks to [@kamilakesbi](https://huggingface.co/kamilakesbi) and [@sanchit-gandhi](https://huggingface.co/sanchit-gandhi) for adding this dataset.
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