印度手语识别和搜索结果

S. Musale, Kalyani Gargate, Vaishnavi Gulavani, Samruddhi Kadam, S. Kothawade
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引用次数: 0

摘要

手语是有听力和语言障碍的人交流的媒介。它使用手势来传递信息。该系统的重点是在搜索引擎中使用手语,帮助残疾人获得他们正在寻找的信息。在这里,我们使用马拉地手语。印度手语的翻译系统不像美国手语那么简单和流行。马拉地语由两个字母组成的单词组成:Swara + Vyanjan (Mulakshar)。每个Vyanjan或Swara都有一个独特的标志,可以用静止帧的图像或视频表示。任何由Swara和Vyanjan组成的字母都是用手势来表示的,如上文所述,在Devnagari文字中,用手势来表示Swara的形状。这些字母用包含特定顺序的动作和帧的视频来表示。此外,可以使用符号搜索在谷歌上搜索预测项。该系统包括三个重要步骤:1)手部检测;2)基于神经网络的符号识别;3)获取搜索结果。总的来说,该系统具有很大的潜力,可以帮助有听力和语言障碍的人通过使用手语在互联网上获取信息。这是机器学习和深度学习技术的一个很有前途的应用。
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Indian sign language recognition and search results
Sign language is a medium of communication for people with hearing and speaking impairment. It uses gestures to convey messages. The proposed system focuses on using sign language in search engines and helping specially-abled people get the information they are looking for. Here, we are using Marathi sign language. Translation systems for Indian sign languages are not much simple and popular as American sign language. Marathi language consists of words with individual letters formed of two letter = Swara + Vyanjan (Mulakshar). Every Vyanjan or Swara individually has a unique sign which can be represented as image or video with still frames. Any letter formed of both Swara and Vyanjan is represented with hand gesture signing the Vyanjan as above and with movement of signed gesture in shape of Swara in Devnagari script. Such letters are represented with videos containing motion and frames in particular sequence. Further the predicted term can be searched on google using the sign search. The proposed system includes three important steps: 1) hand detection; 2) sign recognition using neural networks; 3) fetching search results. Overall, the system has great potential to help individuals with hearing and speaking impairment to access information on the internet through the use of sign language. It is a promising application of machine learning and deep learning techniques.
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CiteScore
0.40
自引率
0.00%
发文量
25
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