印度手语的哑剧识别

Shrivarshaa Sakhamuri, Koppula Praneeta, Pidugu Jahnavi, Anuradha Chinta
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引用次数: 0

摘要

符号是非语言传达的一部分。聋哑人主要使用手语相互交流。对于普通大众来说,与他们交流一直是一项重大挑战,因为手势很难理解。因此,重要的想法是帮助公众和听障人士沟通的缺失。人们开发了各种各样的手语系统,但它们既不灵活,也不划算。因此,本项目提出了一个有效且用户友好的手语识别界面,使听障人士可以轻松地使用Tensorflow, Keras和CNN(卷积神经网络)进行手势识别。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Mime Recognition for Indian Sign Language
Signs are part of non-verbal conveyance. Deaf and mute people primarily use sign language to interact with one another. Communicating with them has always been a significant challenge for the general public, as gestures are difficult to understand. Therefore, the important idea is to assist the com- munication absence among the public and the hearing impaired. Various sign language systems have been developed, but they are neither flexible nor cost-effective. Therefore, this project proposes an effective and user-friendly sign language recognition interface that makes it easy for hearing-impaired people to communicate with the general public using Tensorflow, Keras, and CNN (convolutional neural networks) for gesture recognition.
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