Cultural psychology of english translation through computer vision-based robotic interpretation

IF 1.7 4区 心理学 Q3 PSYCHOLOGY, BIOLOGICAL
Chenxi Li , Hongyao Chen
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引用次数: 0

Abstract

Computer Vision-based English translation approaches pledge robots to master complicated functions. Conversely, the debate remains unanswered as to how to extend persuasion skills to real-world relationships. The stable operation of robots in English translation is an upcoming development in the educational field. The development of science and technology in the form of robots helps in computer vision technology for object detection and learning. In education, the usage of advanced technology is still facing challenges in English translation based on the computer vision of robots. In the article, researchers investigate robotic simulation, movement identification, and target tracking in computer vision, learning from one illustration of the third person's perspective. Researchers consider using a previous information basis like a text repository to deduce the feature to be dealt with as part of a robot to promote its generalization through object detection and learning. A Robot translation based on computer vision of English translation (RT-CV) framework is proposed in the research. Robots' word recognition, facial expression, speech, and movement are captured and based on computer vision; the translation is permitted with the basic functions. RT-CV is implemented in real-world applications with manipulative functions with generalized outcomes. The results are obtained as emotional interaction with robots’ ratio is 87.6%, improving computer vision ratio is 88.7%, the Estimation of translating speed ratio is 84.5%, the efficiency of English translation ratio is 93.8%, and anxiety reduction through communication ratio is 82.2%.

从基于计算机视觉的机器人翻译看英语翻译的文化心理
基于计算机视觉的英语翻译方法保证机器人掌握复杂的功能。相反,关于如何将说服技能扩展到现实世界关系的争论仍然没有答案。机器人在英语翻译中的稳定操作是教育领域即将到来的发展。机器人形式的科学技术的发展有助于物体检测和学习的计算机视觉技术。在教育中,在基于机器人计算机视觉的英语翻译中,先进技术的使用仍然面临挑战。在这篇文章中,研究人员研究了计算机视觉中的机器人模拟、运动识别和目标跟踪,从第三人称视角的一个例子中学习。研究人员考虑使用以前的信息基础,如文本存储库,来推断作为机器人一部分要处理的特征,以通过对象检测和学习来促进其泛化。本研究提出了一种基于计算机视觉的机器人英语翻译(RT-CV)框架。基于计算机视觉捕捉机器人的单词识别、面部表情、语音和动作;翻译的基本功能是允许的。RT-CV是在现实世界的应用程序中实现的,具有通用结果的操纵功能。结果表明,与机器人的情感互动率为87.6%,改善计算机视觉率为88.7%,翻译速度估计率为84.5%,英语翻译效率为93.8%,通过交流减少焦虑率为82.2%。
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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来源期刊
CiteScore
2.90
自引率
0.00%
发文量
53
期刊介绍: Learning and Motivation features original experimental research devoted to the analysis of basic phenomena and mechanisms of learning, memory, and motivation. These studies, involving either animal or human subjects, examine behavioral, biological, and evolutionary influences on the learning and motivation processes, and often report on an integrated series of experiments that advance knowledge in this field. Theoretical papers and shorter reports are also considered.
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