A method for synthetic speech detection using local phase quantization

Due to the convenience of speech synthesis, synthesized disguised speech poses a great threat to the security of speaker verification systems.In order to further enhance the ability of detecting the camouflage to the speaker verification system, a method of synthetic speech detection was put forward...

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Main Authors: Jia XU, Zhihua JIAN, Honghui JIN, Man YANG
Format: Article
Language:zho
Published: Beijing Xintong Media Co., Ltd 2024-02-01
Series:Dianxin kexue
Subjects:
Online Access:http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000-0801.2024024/
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author Jia XU
Zhihua JIAN
Honghui JIN
Man YANG
author_facet Jia XU
Zhihua JIAN
Honghui JIN
Man YANG
author_sort Jia XU
collection DOAJ
description Due to the convenience of speech synthesis, synthesized disguised speech poses a great threat to the security of speaker verification systems.In order to further enhance the ability of detecting the camouflage to the speaker verification system, a method of synthetic speech detection was put forward using the information in spectral domain of the synthetic speech spectrogram.The method employed the local phase quantization (LPQ) algorithm to describe frequency domain information in the speech spectrogram.Firstly, the spectrogram was divided into several sub-blocks, and then the LPQ was performed on each sub-block.After the histogram statistical analysis, the LPQ feature vector was obtained and used as the input feature of the random forest classifier to realize the synthetic speech detection.The experimental results demonstrate that the proposed method further reduces tandem detection cost function (t-DCF) and has better generalization ability.
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institution Kabale University
issn 1000-0801
language zho
publishDate 2024-02-01
publisher Beijing Xintong Media Co., Ltd
record_format Article
series Dianxin kexue
spelling doaj-art-a2dff092e76240adb5623a3f05eb2fd72025-01-15T02:48:34ZzhoBeijing Xintong Media Co., LtdDianxin kexue1000-08012024-02-0140637159555901A method for synthetic speech detection using local phase quantizationJia XUZhihua JIANHonghui JINMan YANGDue to the convenience of speech synthesis, synthesized disguised speech poses a great threat to the security of speaker verification systems.In order to further enhance the ability of detecting the camouflage to the speaker verification system, a method of synthetic speech detection was put forward using the information in spectral domain of the synthetic speech spectrogram.The method employed the local phase quantization (LPQ) algorithm to describe frequency domain information in the speech spectrogram.Firstly, the spectrogram was divided into several sub-blocks, and then the LPQ was performed on each sub-block.After the histogram statistical analysis, the LPQ feature vector was obtained and used as the input feature of the random forest classifier to realize the synthetic speech detection.The experimental results demonstrate that the proposed method further reduces tandem detection cost function (t-DCF) and has better generalization ability.http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000-0801.2024024/speaker verificationspoofing attacksynthetic speech detectionLPQ
spellingShingle Jia XU
Zhihua JIAN
Honghui JIN
Man YANG
A method for synthetic speech detection using local phase quantization
Dianxin kexue
speaker verification
spoofing attack
synthetic speech detection
LPQ
title A method for synthetic speech detection using local phase quantization
title_full A method for synthetic speech detection using local phase quantization
title_fullStr A method for synthetic speech detection using local phase quantization
title_full_unstemmed A method for synthetic speech detection using local phase quantization
title_short A method for synthetic speech detection using local phase quantization
title_sort method for synthetic speech detection using local phase quantization
topic speaker verification
spoofing attack
synthetic speech detection
LPQ
url http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000-0801.2024024/
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