| Challenge: | The video annotation for speech technologies corpus contains 2900 hours of video data . the data are intended to support speech technology development . |
| Approach: | The Video Annotation for Speech Technologies corpus contains 2900 hours of video data . the data are intended to support speech technology development . |
| Outcome: | The video annotation for speech technologies corpus contains 2900 hours of video data . the data are intended to support speech detection, language identification, speaker identification, and speech recognition . |
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Chengyou Wang, Mingchen Shao, Jingbin Hu, Zeyu Zhu, Hongfei Xue, Bingshen Mu, Xin Xu, Xingyi Duan, Binbin Zhang, Zhu Pengcheng, Chuang Ding, Xiaojun Zhang, Hui Bu, Lei Xie
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AnnoTheia: A Semi-Automatic Annotation Toolkit for Audio-Visual Speech Technologies (2024.lrec-main)
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