Proceedings of the 2023 3rd International Conference on Public Management and Intelligent Society (PMIS 2023)

Research on Speech Enhancement Algorithms for Wearable Devices

Authors
Jingze Fu1, Fulang Sun2, *, Hao Yin3, Bingyu Shen4, Zihao Wang5, Hengfan Zhang6
1College of Egr Info & AppSci, Northern Arizona University, Flagstaff, USA
2College of Materials Science and Engineering, Northeastern University, Shenyang, China
3Sino-British College, University of Shanghai for Science and Technology, Shanghai, China
4College of Telecommunications and Information Engineering, Xi’an Jiaotong University, Xi’an, China
5College of Liberal Arts, University of Texas at Austin, Austin, USA
6School Telecommunication Engineering, Xidian University, Xi’an, China
*Corresponding author. Email: 20192934@stu.neu.edu.cn
Corresponding Author
Fulang Sun
Available Online 26 July 2023.
DOI
10.2991/978-94-6463-200-2_101How to use a DOI?
Keywords
enhancement algorithms; deep learning; adaptive noise cancelling; improved adaptive null-forming; LMS
Abstract

Speech is the primary information carrier in human communication and the interference could be caused by environmental noise. The speech enhancement algorithm is an effective method to reduce noise and improve the subjective feeling of the human ear. The existing speech enhancement algorithms can be divided into two categories: single-channel methods and dual-channel methods. This research analyzed the two main digital signal processing topics for speech enhancement algorithms. This included the traditional single channel speech enhancement algorithm and the dual-channel speech enhancement algorithm. The traditional single channel speech enhancement algorithm was further divided into two categories: traditional enhancement algorithms based on digital signal processing and learning enhancement algorithms based on data-driven. The traditional algorithms have limitations in processing non-stationary noise, whereas deep learning has significantly improved handling non-stationary noise. The dual-channel speech enhancement algorithm adds a second microphone to collect noise, providing more real noise for enhancement. This research briefly described the main dual-channel speech enhancement algorithms, including adaptive noise cancelling and first-order difference microphone. In conclusion, the research found that deep learning has shown significant improvement in handling non-stationary noise in single-channel speech enhancement algorithms, and dual-channel speech enhancement algorithms have the potential to provide more real noise for enhancement.

Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 2023 3rd International Conference on Public Management and Intelligent Society (PMIS 2023)
Series
Atlantis Highlights in Intelligent Systems
Publication Date
26 July 2023
ISBN
978-94-6463-200-2
ISSN
2589-4919
DOI
10.2991/978-94-6463-200-2_101How to use a DOI?
Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

TY  - CONF
AU  - Jingze Fu
AU  - Fulang Sun
AU  - Hao Yin
AU  - Bingyu Shen
AU  - Zihao Wang
AU  - Hengfan Zhang
PY  - 2023
DA  - 2023/07/26
TI  - Research on Speech Enhancement Algorithms for Wearable Devices
BT  - Proceedings of the 2023 3rd International Conference on Public Management and Intelligent Society (PMIS 2023)
PB  - Atlantis Press
SP  - 967
EP  - 973
SN  - 2589-4919
UR  - https://doi.org/10.2991/978-94-6463-200-2_101
DO  - 10.2991/978-94-6463-200-2_101
ID  - Fu2023
ER  -