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構音異常溝通輔具之人工智慧系統與晶片
Auditory-Cognition AI System and System-on-Chip Designs for Dysarthria
計畫團隊成員 Members

王進賢特聘教授

Distinguished Prof.

Jinn-Shyan Wang​

國立中正大學電機系&晶研中心

EE Dept. & SoC Research Center, CCU

賴穎暉副教授

Assoc. Prof.

Ying-Hui Lai

國立陽明交通大學生醫系&

晶研中心

BME Dept., NYCU & SoC Research Center

葉經緯教授

Prof. Ching-Wei Yeh

 

國立中正大學電機系&晶研中心

EE Dept. & SoC Research Center, CCU

林泰吉副教授

Assoc. Prof.

Tay-Jyi Lin

國立中正大學資工系&晶研中心

CSIE Dept. & SoC Research Center, CCU

Category
Dysarthria, Artificial Intelligence, Deep Learning, Low Power, System on a Chip
技術亮點
Technical Highlights

技術與產品現況

  1. 未有(構音異常)口譯輔具及概念。
  2. 多數產品著重在電腦字卡輔助患者教育/復健訓練。

成果亮點-關鍵技術

  1. 首創並展示中風與腦麻病患構音異常聲音轉換先例。
  2. 提升VC效益,並降低90%病人訓練負擔。
  3. 進化DNN-Based VC技術為構音異常病患之隨身溝通輔具技術。
  4. 建構單一功能隨身溝通輔具雛形,以成為健保給付之可能或可行方案。
  5. 低功耗DNN設計+低漏電近鄰界電壓電路技術,降低>80%功耗。
 
  • Dysarthria is a common problem of patients with neurological diseases, such as stroke or the Parkinson’s disease, which affects their quality of life.
  • The 4-year project “Auditory-Cognition AI System and System-on-Chip Designs for Dysarthria” will develop AI-based dysarthria-voice-conversion, low-power embedded system, and system-on-a-chip design technologies for achieving the goal of “Speak for Dysarthria.”
  • In the first-year project term, a pure-software-based Dysarthria Voice Conversion (DVC) prototype device running on a 667-MHz-dual-Cortex-A9-Zynq platform has been designed and constructed, which can perform inside tests of converting a dysarthria voice into an intelligible one in less than 1 second.


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