Voiceprint recognition method of optical fiber sensing system based on DTW-GMM

Home > Archive>Volume 38, Issue 4, 2024 >176-186

Voiceprint recognition method of optical fiber sensing system based on DTW-GMM
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                        Yang Jiapei1Yang Jiapei
College of Electronic Information and Optical Engineering, Taiyuan University of Technology, Taiyuan 030024, China
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Wang YuWang Yu
1.College of Electronic Information and Optical Engineering, Taiyuan University of Technology, Taiyuan 030024, China; 2.Key Laboratory of Advanced Transducers and Intelligent Control System, Ministry of Education, Taiyuan University of Technology, Taiyuan 030024, China; 3.Shanxi Transportation Technology Research & Development Company Limited, Taiyuan 030024, China
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Peng Guangjian1Peng Guangjian
College of Electronic Information and Optical Engineering, Taiyuan University of Technology, Taiyuan 030024, China
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Bai QingBai Qing
1.College of Electronic Information and Optical Engineering, Taiyuan University of Technology, Taiyuan 030024, China; 2.Key Laboratory of Advanced Transducers and Intelligent Control System, Ministry of Education, Taiyuan University of Technology, Taiyuan 030024, China; 3.Shanxi Transportation Technology Research & Development Company Limited, Taiyuan 030024, China
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Liu XinLiu Xin
1.College of Electronic Information and Optical Engineering, Taiyuan University of Technology, Taiyuan 030024, China; 2.Key Laboratory of Advanced Transducers and Intelligent Control System, Ministry of Education, Taiyuan University of Technology, Taiyuan 030024, China; 3.Shanxi Transportation Technology Research & Development Company Limited, Taiyuan 030024, China
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Jin BaoquanJin Baoquan
1.College of Electronic Information and Optical Engineering, Taiyuan University of Technology, Taiyuan 030024, China; 2.Key Laboratory of Advanced Transducers and Intelligent Control System, Ministry of Education, Taiyuan University of Technology, Taiyuan 030024, China
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Affiliation:1.College of Electronic Information and Optical Engineering, Taiyuan University of Technology, Taiyuan 030024, China; 2.Key Laboratory of Advanced Transducers and Intelligent Control System, Ministry of Education, Taiyuan University of Technology, Taiyuan 030024, China; 3.Shanxi Transportation Technology Research & Development Company Limited, Taiyuan 030024, China
Clc Number:TH741
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Abstract:

In order to meet the demand of voiceprint recognition in flammable and explosive environment. A linear Sagnac interference optical fiber acoustic sensor system has been designed. Speech data was denoised using the Wiener filtering algorithm, and pitch features were extracted through three-level clipping. Speaker samples were screened using dynamic time warping, and Mel-frequency cepstral coefficients were extracted as features. Voiceprint recognition experiments were conducted utilizing the Gaussian mixture model-expectation maximization algorithm, concurrently investigating the frequency response characteristics of the optical fiber acoustic sensor system and their relationship with voiceprint features. The influence of the amplitude of acquired speech on voiceprint recognition outcomes was studied. Experimental results demonstrate that the system can realize the sound signal perception in the frequency range of 300~3 500 Hz. When the sound amplitude decreases from 0.9 to 0.15 V, the difference between the maximum and second-largest log-likelihood values drops from 35.5 to 10.9, the recognition result changed from success to failure. Repetition experiments show that, at a distance of 2 meters from the sound source along a 10-kilometer sensing fiber, the system accurately recognizes 400 speech segments of 3 to 5 seconds duration, unrelated to any specific text, achieving an overall identification accuracy rate of 94.75%. This system holds promise as a solution for voiceprint recognition in applications such as equipment fault diagnosis and emergency response within flammable and explosive environments.

Key words:optical fiber sensing; Sagnac interference; voiceprint recognition; Gaussian mixture model

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Online: July 02,2024
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