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                            雙語新聞:把手語翻譯成語音!清華北航兩名90后女生發明翻譯臂環

                            青島希尼爾翻譯咨詢有限公司(www.jdzzqp.icu)整理發布  2017-05-28

                              

                            青島希尼爾翻譯公司(www.jdzzqp.icu)2017年5月28日了解到:After National Disabled Person’s Day on May 21, a video released by CCTV featuring two graduate students from Beihang University and Tsinghua University has gone viral online. 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. The pair won first prize last month in an open design challenge organized by the UN Development Program and tech giant Baidu.

                            繼“全國助殘日”過后,中央電視臺發布的一則視頻在5月21日前后迅速在網上流傳起來。該視頻的主人公是兩位研究生——來自北京航空航天大學的王娜娜和來自清華大學的黃爽,兩位同學為了幫助自己聽力受損的朋友,研究發明了一種能將手語轉換為語音的翻譯臂環。與此同時,她們還于上個月在在聯合國和百度公司共同舉辦的設計挑戰大賽上憑借該發明奪得冠軍。

                            Wang Nana started her research with a goal of helping the disabled rather than making a fortune. 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. She felt sorry for Zhang when, surrounded by a chatting group, he could only remain silent.

                            事實上,王娜娜最初設計翻譯臂環的初衷并非為了盈利,只是單純想幫助那些在這方面有缺陷的殘疾群體。王娜娜有一位聾人朋友叫張權,由于她自己不懂手語,平時即使兩人坐在一起,張權也不得不用微信打字和她交流。特別當許多人一起聊天時,她更為身處無聲世界的張權感到抱歉。

                            At the time, Wang was a computer science student studying image-based sign language recognition technology. 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.

                            當時,計算機專業的王娜娜正在研究基于圖像的手勢識別技術。然而,她本人將注意力過多放在考慮該翻譯裝置可攜帶性的相關技術細節之上,后來還是娜娜的好朋友黃爽提醒她可以嘗試發明可佩帶的裝置。

                            The idea for a sign language armband was inspired by a device used by student musicians studying piano. Teachers can tell whether the muscles in a student’s arm are properly aligned through the use of special armbands. 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. In this way, people dependent on sign language to communicate can "speak" fluently with ordinary people.

                            后來,王娜娜了解到有一種專門用于學習鋼琴的臂環,鋼琴老師通過看肌肉的用力情況來判斷學生的指法是否正確,這一裝置恰好為王娜娜提供了靈感。隨后,娜娜和黃爽兩人便決定將該項技術運用到自己的新裝置之上,她們將每個手語詞匯的肌肉電信號錄入系統,讓人工智能深度學習,以便系統在下次遇見相應手語之后可進行識別和轉化成語音。通過這種方式,那些依賴手語交流的群體今后將有可能做到和正常人一樣流暢“對話”。
                            來源:人民網

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