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Anim-400K: A dataset designed from the ground up for automated dubbing of video
What is Anim-400K?
Anim-400K is a large-scale dataset of aligned audio-video clips in both the English and Japanese languages. It is comprised of over 425K aligned clips (763 hours) consisting of both video and audio drawn from over 190 properties covering hundreds of themes and genres. Anim400K is further augmented with metadata including genres, themes, show-ratings, character profiles, and animation styles at a property level, episode synopses, ratings, and subtitles at an episode level, and pre-computed ASR at an aligned clip level to enable in-depth research into several audio-visual tasks.
Read the [ArXiv Preprint]
Check us out on [Github]
News
[January 2024] Anim-400K (v1) available on Huggingface Datasets.
[January 2024] Anim-400K (v1) release.
[January 2024] Anim-400K (v1) accepted at ICASSP2024.
Citation
If any part of our paper is helpful to your work, please cite with:
@inproceedings{cai2024anim400k,
title={ANIM-400K: A Large-Scale Dataset for Automated End to End Dubbing of Video},
author={Cai, Kevin and Liu, Chonghua and Chan, David M.},
booktitle={ICASSP 2024-2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
pages={1--5},
year={2024},
organization={IEEE}
}
Acknowledgements
This repository, and data release model is modeled on that used by the MAD dataset.
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