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App. Res. of Comp. Accepted Paper
Vol. 41, 2024 No. 11

Spoken term detection and fine-grained localization method based on multi-scale distance matrices

Li Xiangrui1
Mao Qirong1,2
1. Jiangsu University, School of Computer Science & Communication Engineering, Zhenjiang Jiangsu 212013, China
2. Jiangsu Province Big Data Ubiquitous Perception & Intelligent Agriculture Application Engineering Research Center, Zhenjiang Jiangsu 212013, China
DOI: 10.19734/j.issn.1001-3695.2024.03.0097

Abstract

Aiming to address the low localization accuracy of existing spoken term detection methods, a spoken term detection and fine-grained localization method based on multi-scale distance matrices (MF-STD) is proposed. This method first employs a residual convolutional network to extract features and construct a distance matrix to model the correlation between inputs. Then, it learns the localization information at different scales through multi-scale segmentation and decoupling heads. Finally, the model is optimized according to the multi-scale weighted localization loss, confidence loss, and classification loss. This enables the model to achieve fine-grained prediction of keyword existence and time domain boundaries. Experimental results on the LibriSpeech dataset demonstrate that for in-vocabulary detection, the precision and intersection over union (IoU) reach 97.1% and 88.6%, respectively. In the case of out-of-vocabulary detection, the precision and IoU reach 96.7% and 88.2%, respectively. In comparison to existing methods for spoken term detection and localization, MF-STD significantly improves detection accuracy and localization precision. This fully demonstrates the superiority of the proposed method and the effectiveness of multi-scale feature modeling and fine-grained localization constraints in spoken term detection tasks.

Foundation Support

江苏省重点研发计划(BE2020036)、江苏大学应急管理学院专项科研项目(KY-A-01)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2024.03.0097
Publish at: Application Research of Computers Accepted Paper, Vol. 41, 2024 No. 11

Publish History

[2024-08-05] Accepted Paper

Cite This Article

李祥瑞, 毛启容. 基于多尺度距离矩阵的语音关键词检测与细粒度定位方法 [J]. 计算机应用研究, 2024, 41 (11). (2024-09-11). https://doi.org/10.19734/j.issn.1001-3695.2024.03.0097. (Li Xiangrui, Mao Qirong. Spoken term detection and fine-grained localization method based on multi-scale distance matrices [J]. Application Research of Computers, 2024, 41 (11). (2024-09-11). https://doi.org/10.19734/j.issn.1001-3695.2024.03.0097. )

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.

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