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American and Russian Sign Language Dactyl Recognition and Text2Sign Translation

机译:美国和俄罗斯手语手势识别和Text2Sign翻译

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Sign language is the main way to communicate for people from deaf community. However, common people mostly do not know sign language. In this paper, we overview several real-time sign language dactyl recognition systems using deep convolutional neural networks. These systems are able to recognize dactylized words gestured by signs for each letter. We evaluate our approach on American (ASL) and Russian (RSL) sign languages. This solution may help fasten the process of communication for deaf people. On the contrary, we also present the algorithm for generating sign animation from text information using text-to-sign video vocabulary, which helps to integrate sign language in dubbed TV and combining with speech recognition tool provide full translation from natural language to sign language.
机译:手语是聋人社区与人交流的主要方式。但是,普通百姓大多不懂手语。在本文中,我们概述了使用深度卷积神经网络的几种实时手语指纹识别系统。这些系统能够识别由每个字母的符号打手势的精制单词。我们评估了我们对美国(ASL)和俄罗斯(RSL)手语的处理方式。该解决方案可以帮助加快聋人的沟通过程。相反,我们还提出了使用文本到符号视频词汇从文本信息中生成符号动画的算法,该算法有助于将符号语言集成到配音电视中,并与语音识别工具结合使用,可以将自然语言完全翻译为符号语言。

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