AVSpeech: Large-scale Audio-Visual Speech Dataset
Ariel Ephrat and Inbar Mosseri and Oran Lang and Tali Dekel and Kevin Wilson and Avinatan Hassidim and William T. Freeman and Michael Rubinstein

AVSpeech (402 files)
metadata.jsonl.zip 133.32MB
clips/xpi.tar 3.70GB
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clips/xnn.tar 3.58GB
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Type: Dataset
Tags: speech isolation, lip reading, face detection

Bibtex:
@article{,
title= {AVSpeech: Large-scale Audio-Visual Speech Dataset },
journal= {},
author= {Ariel Ephrat and Inbar Mosseri and Oran Lang and Tali Dekel and Kevin Wilson and Avinatan Hassidim and William T. Freeman and Michael Rubinstein},
year= {},
url= {https://looking-to-listen.github.io/avspeech/},
abstract= {AVSpeech is a new, large-scale audio-visual dataset comprising speech video clips with no interfering background noises. The segments are 3-10 seconds long, and in each clip the audible sound in the soundtrack belongs to a single speaking person, visible in the video. In total, the dataset contains roughly 4700 hours* of video segments, from a total of 290k YouTube videos, spanning a wide variety of people, languages and face poses. For more details on how we created the dataset see our paper, Looking to Listen at the Cocktail Party: A Speaker-Independent Audio-Visual Model for Speech Separation (https://arxiv.org/abs/1804.03619).

* UPLOADER'S NOTE: This dataset contains 3000 hours of video segments and not the entire 4700 hours. 1700 hours were not included as some no longer existed on youtube, had a copyright violation, not available in the United States, or was of poor quality. Over 1 million segments are included in this torrent, each between 3 - 10 seconds, and in 720p resolution. See README on how to use this dataset},
keywords= {speech isolation, lip reading, face detection},
terms= {},
license= {},
superseded= {}
}


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