Tay-Jyi Lin, Chen-Zong Liao, You-Jia Hu, Wei-Cheng Hsu, Zheng-Xian Wu, Shao-Yu Wang, Chun-Ming Huang, Ying-Hui Lai, C. Yeh, Jinn-Shyan Wang
{"title":"A 40nm CMOS SoC for Real-Time Dysarthric Voice Conversion of Stroke Patients","authors":"Tay-Jyi Lin, Chen-Zong Liao, You-Jia Hu, Wei-Cheng Hsu, Zheng-Xian Wu, Shao-Yu Wang, Chun-Ming Huang, Ying-Hui Lai, C. Yeh, Jinn-Shyan Wang","doi":"10.1109/ASP-DAC52403.2022.9712584","DOIUrl":null,"url":null,"abstract":"This paper presents the first dysarthric voice conversion SoC, which can translate stroke patients' voice into more intelligible and clearer speech in real time. The SoC is composed of a RISC-V MPU and a compact DNN engine with a single 16-bit multiply-accumulator, which improves 12x performance and > 100x energy efficiency, and has been implemented in 40nm CMOS. The silicon area is 0.68×0.79mm2, and the measured power is 18.4mW for converting 3-sec dysarthric voice within 0.5 sec (at 200MHz and 0.8V) and 4.8mW for conversion < 1 sec (at 100MHz and 0.6V).","PeriodicalId":239260,"journal":{"name":"2022 27th Asia and South Pacific Design Automation Conference (ASP-DAC)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 27th Asia and South Pacific Design Automation Conference (ASP-DAC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ASP-DAC52403.2022.9712584","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This paper presents the first dysarthric voice conversion SoC, which can translate stroke patients' voice into more intelligible and clearer speech in real time. The SoC is composed of a RISC-V MPU and a compact DNN engine with a single 16-bit multiply-accumulator, which improves 12x performance and > 100x energy efficiency, and has been implemented in 40nm CMOS. The silicon area is 0.68×0.79mm2, and the measured power is 18.4mW for converting 3-sec dysarthric voice within 0.5 sec (at 200MHz and 0.8V) and 4.8mW for conversion < 1 sec (at 100MHz and 0.6V).