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名校女学霸研发出手语翻译臂环_亚搏网页登录
时间:2021-03-03 来源:亚博网页版登陆 浏览量 38266 次
本文摘要:After National Disabled Persons Day on May 21, a video released by CCTV featuring two graduate students from Beihang University and Tsinghua University has gone viral online.在5月21日“全国助残日”以后,央视发布的一段相关俩位来源于苏大、清华大学的大学毕业生的视頻,迅速在网络上广为流传一起。

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After National Disabled Persons Day on May 21, a video released by CCTV featuring two graduate students from Beihang University and Tsinghua University has gone viral online.在5月21日“全国助残日”以后,央视发布的一段相关俩位来源于苏大、清华大学的大学毕业生的视頻,迅速在网络上广为流传一起。Wang Nana and Huang Shuang, intent on helping their hearing-impaired friends, invented a wearable sign-language interpreter by transforming sign language into audible information.王娜娜白心爽为了更好地帮助自身英语听力毁损的盆友,科学研究发明人了一种能将手语转换为视频语音的译成臂环。The pair won first prize last month in an open design challenge organized by the UN Development Program and tech giant Baidu.他们还于上月在联合国开发计划署和互联网巨头百度分公司协同举办的设计方案挑戰比赛上斩获了总冠军。

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Wang Nana started her research with a goal of helping the disabled rather than making a fortune.王娜娜刚开始这一科学研究的念头并不是为了更好地赢利,仅仅要想帮助残废人群。Her friend, Zhang Quan, could only use WeChat to communicate with her even when they were sitting face to face, as Wang did not know sign language.她的一位名叫张权的聋人盆友,因为王娜娜不明白手语,因此 平常即便两个人零距离躺在一起,张权也迫不得已用微信点字和她沟通交流。She felt sorry for Zhang when, surrounded by a chatting group, he could only remain silent.当很多人 一起闲聊时,张权不可以装聋作哑,她就倍感伤心。At the time, Wang was a computer science student studying image-based sign language recognition technology.那时候,软件工程专业的王娜娜已经科学研究根据图象的手式识别技术性。

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However, she was too focused on technical details to consider the portability of an interpretation device. It was her close friend Huang Shuang who contributed the idea of creating something wearable.但是,她自己将专注力过多放进充分考虑该译成装置可带上性的涉及到关键技术以上,之后還是她的最好的朋友黄爽警示她能够试着发明人可佩戴的装置。The idea for a sign language armband was inspired by a device used by student musicians studying piano.手语臂环的好点子,是遭受自学钢琴的学员乐手们用以的一个武器装备的设计灵感。Teachers can tell whether the muscles in a students arm are properly aligned through the use of special armbands.教师能够根据这一相近臂环的用以,鉴别出有学员手臂上的全身肌肉否均衡使力。

Wang and Huang decided to apply this technology to their device. They put each neuromuscular signal of sign language into a system, and then employed artificial intelligence to help the system recognize and translate the signs into audible information.接着,霏霏白心爽两个人以后规定将此项技术性应用到自身的装置以上,他们将每一个手语语汇的全身肌肉电子信号加载系统软件,让人工智能技术深层通过自学,便于系统软件在下一次偶遇适度手语以后可进行识别和转换成视频语音。In this way, people dependent on sign language to communicate can speak fluently with ordinary people.根据这类方法,这些仰仗手语沟通交流的人群将来将有可能做和平常人一样简约“会话”。


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