In accordance with regulations and requirements, the editorial department's website domain has been changed to arocmag.cn. The original domain (arocmag.com) will be discontinued after Dec. 31st, 2024.
See More
App. Res. of Comp. Accepted Paper
Vol. 41, 2024 No. 11

Adaptive rank constrained inverse matrix approximation decomposition method and its application in speech enhancement

Wang Qiangjin1,2,3
Wu Zhantao1,2,3
Li Baoqing1,2
Yang Yu1,2
1. College of Mechanical & Vehicle Engineering, Hunan University, Changsha 410000, China
2. Hunan Provincial Key Laboratory of Equipment Service Quality Assurance, Hunan University, Changsha 410000, China
3. Hunan Provincial Key Laboratory of Construction Machinery Intelligence Technology Based on the Internet of Things, Hunan University Changsha 410000, China
DOI: 10.19734/j.issn.1001-3695.2024.03.0078

Abstract

This paper proposed a new matrix decomposition method Adaptive Rank Constrained Inverse Matrix Approximation(ARCIMA) to address issues in the Constrained Low-rank and Sparse Matrix Decomposition (CLSMD) approach, where hard thresholding could lead to loss of speech signal components or isolated noise problems. Initially, the energy threshold method estimated the rank of the low-rank matrix. Then, considering the structural characteristics of the speech signal subspace matrix, the Modified Bilateral Random Projections(MBRP) method solved the low-rank matrix representing the clean speech signal, reducing the computational load compared to the SVD method. Tikhonov regularization optimized the solution's stability during iterative solving. Experimental results show that this method achieves better PESQ scores in various noisy environments compared to classical methods, and the enhanced speech waveform is closer to the original speech waveform. The method demonstrates superior denoising performance under low signal-to-noise ratio conditions.

Foundation Support

国家自然科学基金资助项目(51975193)
湖南省普通高等学校教学改革研究项目(HNJG-2022-0520)
湖南大学本科教育教学改革专项(2024)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2024.03.0078
Publish at: Application Research of Computers Accepted Paper, Vol. 41, 2024 No. 11

Publish History

[2024-07-23] Accepted Paper

Cite This Article

王强进, 吴占涛, 李宝庆, 等. 自适应秩约束逆矩阵近似分解及其在语音增强中的应用 [J]. 计算机应用研究, 2024, 41 (11). (2024-09-11). https://doi.org/10.19734/j.issn.1001-3695.2024.03.0078. (Wang Qiangjin, Wu Zhantao, Li Baoqing, et al. Adaptive rank constrained inverse matrix approximation decomposition method and its application in speech enhancement [J]. Application Research of Computers, 2024, 41 (11). (2024-09-11). https://doi.org/10.19734/j.issn.1001-3695.2024.03.0078. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

Indexed & Evaluation

  • The Second National Periodical Award 100 Key Journals
  • Double Effect Journal of China Journal Formation
  • the Core Journal of China (Peking University 2023 Edition)
  • the Core Journal for Science
  • Chinese Science Citation Database (CSCD) Source Journals
  • RCCSE Chinese Core Academic Journals
  • Journal of China Computer Federation
  • 2020-2022 The World Journal Clout Index (WJCI) Report of Scientific and Technological Periodicals
  • Full-text Source Journal of China Science and Technology Periodicals Database
  • Source Journal of China Academic Journals Comprehensive Evaluation Database
  • Source Journals of China Academic Journals (CD-ROM Version), China Journal Network
  • 2017-2019 China Outstanding Academic Journals with International Influence (Natural Science and Engineering Technology)
  • Source Journal of Top Academic Papers (F5000) Program of China's Excellent Science and Technology Journals
  • Source Journal of China Engineering Technology Electronic Information Network and Electronic Technology Literature Database
  • Source Journal of British Science Digest (INSPEC)
  • Japan Science and Technology Agency (JST) Source Journal
  • Russian Journal of Abstracts (AJ, VINITI) Source Journals
  • Full-text Journal of EBSCO, USA
  • Cambridge Scientific Abstracts (Natural Sciences) (CSA(NS)) core journals
  • Poland Copernicus Index (IC)
  • Ulrichsweb (USA)