Your browser doesn't support javascript.
loading
Implementation of Sound Direction Detection and Mixed Source Separation in Embedded Systems.
Wang, Jian-Hong; Le, Phuong Thi; Bee, Weng-Sheng; Putri, Wenny Ramadha; Su, Ming-Hsiang; Li, Kuo-Chen; Chen, Shih-Lun; He, Ji-Long; Pham, Tuan; Li, Yung-Hui; Wang, Jia-Ching.
Affiliation
  • Wang JH; School of Computer Science and Technology, Shandong University of Technology, Zibo 255000, China.
  • Le PT; Department of Computer Science and Information Engineering, Fu Jen Catholic University, New Taipei City 242062, Taiwan.
  • Bee WS; Department of Computer Science and Information Engineering, National Central University, Taoyuan City 320314, Taiwan.
  • Putri WR; Department of Computer Science and Information Engineering, National Central University, Taoyuan City 320314, Taiwan.
  • Su MH; Department of Data Science, Soochow University, Taipei City 10048, Taiwan.
  • Li KC; Department of Information Management, Chung Yuan Christian University, Taoyuan City 320317, Taiwan.
  • Chen SL; Department of Electronic Engineering, Chung Yuan Christian University, Taoyuan City 320314, Taiwan.
  • He JL; School of Computer Science and Technology, Shandong University of Technology, Zibo 255000, China.
  • Pham T; Faculty of Digital Technology, University of Technology and Education-University of Dà Nang, Danang 550000, Vietnam.
  • Li YH; AI Research Center, Hon Hai Research Institute, New Taipei City 207236, Taiwan.
  • Wang JC; Department of Computer Science and Information Engineering, National Central University, Taoyuan City 320314, Taiwan.
Sensors (Basel) ; 24(13)2024 Jul 04.
Article in En | MEDLINE | ID: mdl-39001130
ABSTRACT
In recent years, embedded system technologies and products for sensor networks and wearable devices used for monitoring people's activities and health have become the focus of the global IT industry. In order to enhance the speech recognition capabilities of wearable devices, this article discusses the implementation of audio positioning and enhancement in embedded systems using embedded algorithms for direction detection and mixed source separation. The two algorithms are implemented using different embedded systems direction detection developed using TI TMS320C6713 DSK and mixed source separation developed using Raspberry Pi 2. For mixed source separation, in the first experiment, the average signal-to-interference ratio (SIR) at 1 m and 2 m distances was 16.72 and 15.76, respectively. In the second experiment, when evaluated using speech recognition, the algorithm improved speech recognition accuracy to 95%.
Subject(s)
Key words

Full text: 1 Database: MEDLINE Main subject: Algorithms / Wearable Electronic Devices Limits: Humans Language: En Journal: Sensors (Basel) Year: 2024 Type: Article Affiliation country: China

Full text: 1 Database: MEDLINE Main subject: Algorithms / Wearable Electronic Devices Limits: Humans Language: En Journal: Sensors (Basel) Year: 2024 Type: Article Affiliation country: China