Smart Translation for Physically Challenged People Using Machine Learning

Ramakrishna Hegde, R. M. Chitrashree, N. Dimple, Harshitha G Shet, J. Deekshitha, S. M. Soumyasri
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引用次数: 2

Abstract

In sign language, hand motions are one of the nonverbal communication modalities employed. It is most typically used by deaf and hard of hearing persons who have hearing or speech impairments. Difficulties communicating with one another or with regular people folks. Several sign language systems have been created by There are numerous producers all throughout the world, but they are neither versatile nor adaptable, end-user-friendly in terms of price. Our project's goal is to create a feasible system for communication for deaf people. This project is divided into two sections. (1) It translates an audio message into sign language, and (2) it translates images/video into text/speech. The first category we'll take input as audio, turns the audio recorded message into text message, and later displays predetermined Indian Sign Language(ISL) visuals or GIFs. The use of this technique facilitates communication between hearing and deaf persons. In the second category, we will gather photographs and train images with CNN and present the results.
使用机器学习为残疾人提供智能翻译
在手语中,手势是一种非语言交流方式。它最典型地用于有听力或语言障碍的聋人和重听人。与他人或与普通人沟通困难。世界各地有许多制造商创造了几种手语系统,但它们既不通用也不适应性强,在价格方面最终用户友好。我们项目的目标是为聋哑人创造一个可行的交流系统。本项目分为两个部分。(1)将音频信息翻译成手语;(2)将图像/视频翻译成文本/语音。在第一类中,我们将输入为音频,将录制的音频信息转换为文本信息,然后显示预定的印度手语(ISL)视觉效果或gif。这种技术的使用促进了听人和聋人之间的交流。在第二类中,我们将使用CNN收集照片和训练图像并呈现结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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