A playback speech detection algorithm based on log inverse Mel-frequency spectral coefficient
The popularity and portability of high-fidelity audio recording equipment and playback equipment poses a serious challenge for speaker recognition systems against playback attacks.Based on the differences between the original speech and the playback speech in high frequency region,the algorithm reve...
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Format: | Article |
Language: | zho |
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Beijing Xintong Media Co., Ltd
2018-05-01
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Series: | Dianxin kexue |
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Online Access: | http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000-0801.2018020/ |
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author | Lang LIN Rangding WANG Diqun YAN Can LI |
author_facet | Lang LIN Rangding WANG Diqun YAN Can LI |
author_sort | Lang LIN |
collection | DOAJ |
description | The popularity and portability of high-fidelity audio recording equipment and playback equipment poses a serious challenge for speaker recognition systems against playback attacks.Based on the differences between the original speech and the playback speech in high frequency region,the algorithm reversed the Mel-filter bank in Mel-frequency cepstral coefficient (MFCC) calculation,and the coefficients before the DCT were used as the features of the algorithm.SVM was utilized as the classifier.Experimental results show that this algorithm can effectively detect the playback speech.In addition,the algorithm is integrated into the GMM-UBM speaker recognition system,which significantly improves the systems’ capability of resisting the playback attack. |
format | Article |
id | doaj-art-c26f476a2ac8483d924c499382cd9d17 |
institution | Kabale University |
issn | 1000-0801 |
language | zho |
publishDate | 2018-05-01 |
publisher | Beijing Xintong Media Co., Ltd |
record_format | Article |
series | Dianxin kexue |
spelling | doaj-art-c26f476a2ac8483d924c499382cd9d172025-01-15T03:25:19ZzhoBeijing Xintong Media Co., LtdDianxin kexue1000-08012018-05-0134909859801888A playback speech detection algorithm based on log inverse Mel-frequency spectral coefficientLang LINRangding WANGDiqun YANCan LIThe popularity and portability of high-fidelity audio recording equipment and playback equipment poses a serious challenge for speaker recognition systems against playback attacks.Based on the differences between the original speech and the playback speech in high frequency region,the algorithm reversed the Mel-filter bank in Mel-frequency cepstral coefficient (MFCC) calculation,and the coefficients before the DCT were used as the features of the algorithm.SVM was utilized as the classifier.Experimental results show that this algorithm can effectively detect the playback speech.In addition,the algorithm is integrated into the GMM-UBM speaker recognition system,which significantly improves the systems’ capability of resisting the playback attack.http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000-0801.2018020/speaker recognitionplayback speech detectionlog Mel-frequency spectruminverse Mel-filter group |
spellingShingle | Lang LIN Rangding WANG Diqun YAN Can LI A playback speech detection algorithm based on log inverse Mel-frequency spectral coefficient Dianxin kexue speaker recognition playback speech detection log Mel-frequency spectrum inverse Mel-filter group |
title | A playback speech detection algorithm based on log inverse Mel-frequency spectral coefficient |
title_full | A playback speech detection algorithm based on log inverse Mel-frequency spectral coefficient |
title_fullStr | A playback speech detection algorithm based on log inverse Mel-frequency spectral coefficient |
title_full_unstemmed | A playback speech detection algorithm based on log inverse Mel-frequency spectral coefficient |
title_short | A playback speech detection algorithm based on log inverse Mel-frequency spectral coefficient |
title_sort | playback speech detection algorithm based on log inverse mel frequency spectral coefficient |
topic | speaker recognition playback speech detection log Mel-frequency spectrum inverse Mel-filter group |
url | http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000-0801.2018020/ |
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