This paper presents our recent developments in the automatic processing of sign language corpora using the Hamburg Sign Language Annotation System (HamNoSys). We designed an automated tool to convert HamNoSys annotations into numerical labels for defined initial features of body and hand positions. Our proposed numerical multilabels greatly simplify annotations' structure without significant loss of gloss meaning. These numerical multilabels can potentially be used to feed the machine learning models, which would accelerate the development of vision-based sign language recognition. In addition, this tool can assist experts in the annotation process and help identify semantic errors. The code and sample annotations are publicly available at \url{https://github.com/hearai/parse-hamnosys}.
翻译:本文件介绍我们利用汉堡手语说明系统(HamnoSys)自动处理手语公司的最新发展情况。我们设计了一个自动化工具,将HamNoSys说明转换为用于确定身体和手势位置初始特征的数字标签。我们提议的数字多标签大大简化了说明的结构,但不会大大丧失光滑的含义。这些数字多标签可以用来为机器学习模型提供材料,加速基于视觉的手语识别。此外,这一工具可以帮助笔记过程的专家,并有助于识别语义错误。代码和样本说明可在以下网站公开查阅:https://github.com/heareai/parse-hamnosys}。