American and Russian Sign Language Dactyl Recognition and Text2Sign Translation

被引:3
|
作者
Makarov, Ilya [1 ]
Veldyaykin, Nikolay [1 ]
Chertkov, Maxim [1 ]
Pokoev, Aleksei [1 ]
机构
[1] Natl Res Univ Higher Sch Econ, Moscow, Russia
基金
俄罗斯科学基金会;
关键词
Sign language translation; Russian Sign Language; American Sign Language; Hand gesture recognition; Deep convolutional neural networks; GESTURE RECOGNITION;
D O I
10.1007/978-3-030-37334-4_28
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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.
引用
收藏
页码:309 / 320
页数:12
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