SeeHear: Signer Diarisation and a New Dataset
SeeHear: Signer Diarisation and a New Dataset
复制标题
DOI：
10.1109/icassp39728.2021.9414856
复制
发表时间：
2021-06
期刊：
影响因子：
--
通讯作者：
Samuel Albanie;Gül Varol;Liliane Momeni;Triantafyllos Afouras;Andrew Brown;Chuhan Zhang;Ernesto Coto;Necati Cihan Camgöz;Ben Saunders;Abhishek Dutta;Neil Fox;R. Bowden;B. Woll;Andrew Zisserman
中科院分区：
文献类型：
--
作者：
Samuel Albanie;Gül Varol;Liliane Momeni;Triantafyllos Afouras;Andrew Brown;Chuhan Zhang;Ernesto Coto;Necati Cihan Camgöz;Ben Saunders;Abhishek Dutta;Neil Fox;R. Bowden;B. Woll;Andrew Zisserman
在这项工作中，我们提出了一个框架来收集大规模、多样化的手语数据集，用于训练自动手语识别模型。这项工作的第一个贡献是SDTrack，一个在野外跟踪和记录手语的通用方法。我们的第二个贡献是SEEHAR，这是一个90小时的英国手语(BSL)内容数据集，有1000多名签名者，包括采访、独白和辩论。使用SDTrack，SEEHER数据集使用35K个活动签名轨迹、相应的签名者身份和字幕以及40K个自动本地化的签名标签进行注释。作为第三个贡献，我们为SEEHAR上的签名者日记和手语识别提供了基准。
In this work, we propose a framework to collect a large-scale, diverse sign language dataset that can be used to train automatic sign language recognition models.The first contribution of this work is SDTrack, a generic method for signer tracking and diarisation in the wild. Our second contribution is SeeHear, a dataset of 90 hours of British Sign Language (BSL) content featuring more than 1000 signers, and including interviews, monologues and debates. Using SDTrack, the SeeHear dataset is annotated with 35K active signing tracks, with corresponding signer identities and subtitles, and 40K automatically localised sign labels. As a third contribution, we provide benchmarks for signer diarisation and sign recognition on SeeHear.