Speech signal authentication and self-recovery based on DTWT and ADPCM.
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| Title: | Speech signal authentication and self-recovery based on DTWT and ADPCM. |
|---|---|
| Authors: | Quiñonez-Carbajal, Maria T.1 (AUTHOR), Reyes-Reyes, Rogelio1 (AUTHOR), Ponomaryov, Volodymyr1 (AUTHOR), Cruz-Ramos, Clara1 (AUTHOR) ccruzra@ipn.mx, Garcia-Salgado, Beatriz P.1 (AUTHOR) |
| Source: | Multimedia Tools & Applications. Sep2024, Vol. 83 Issue 31, p76341-76365. 25p. |
| Subjects: | Adaptive modulation, Discrete wavelet transforms, Digital watermarking, Speech, Wavelet transforms, Signal-to-noise ratio |
| Abstract: | The digital voice is multimedia content of great importance, given the range of applications where it can be found. This paper addresses the shortcomings of existing voice authentication algorithms, presenting a completely blind speech authentication and recovery method based on fragile watermarking using the Least Significant Bit (LSB) method. This scheme obtains a compressed version of the original speech signal by Adaptive Differential Pulse Code Modulation (ADPCM) coding and the Discrete-Time Wavelet Transform (DTWT). Authentication bits are then generated by the SHA256 hash function, and the watermark is afterward embedded in the last three LSBs of the original audio samples. Experimental results evaluated on five different audio databases, each comprising speech signals recorded in different situations, contexts, and languages, have demonstrated a high embedding payload and imperceptibility of the watermark, obtaining an average Signal-to-Noise Ratio (SNR) value above 40 d B . Furthermore, the proposed method demonstrates a strong ability to accurately locate and restore up to 50% of a speech signal that has been tampered with, using no additional information. Moreover, the recovered speech signal is intelligible and has an SNR value higher than other recovery schemes, justifying the efficiency of the proposed method. [ABSTRACT FROM AUTHOR] |
| Copyright of Multimedia Tools & Applications is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
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| Header | DbId: egs DbLabel: Engineering Source An: 179414571 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Speech signal authentication and self-recovery based on DTWT and ADPCM. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Quiñonez-Carbajal%2C+Maria+T%2E%22">Quiñonez-Carbajal, Maria T.</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Reyes-Reyes%2C+Rogelio%22">Reyes-Reyes, Rogelio</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Ponomaryov%2C+Volodymyr%22">Ponomaryov, Volodymyr</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Cruz-Ramos%2C+Clara%22">Cruz-Ramos, Clara</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> ccruzra@ipn.mx</i><br /><searchLink fieldCode="AR" term="%22Garcia-Salgado%2C+Beatriz+P%2E%22">Garcia-Salgado, Beatriz P.</searchLink><relatesTo>1</relatesTo> (AUTHOR) – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Multimedia+Tools+%26+Applications%22">Multimedia Tools & Applications</searchLink>. Sep2024, Vol. 83 Issue 31, p76341-76365. 25p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Adaptive+modulation%22">Adaptive modulation</searchLink><br /><searchLink fieldCode="DE" term="%22Discrete+wavelet+transforms%22">Discrete wavelet transforms</searchLink><br /><searchLink fieldCode="DE" term="%22Digital+watermarking%22">Digital watermarking</searchLink><br /><searchLink fieldCode="DE" term="%22Speech%22">Speech</searchLink><br /><searchLink fieldCode="DE" term="%22Wavelet+transforms%22">Wavelet transforms</searchLink><br /><searchLink fieldCode="DE" term="%22Signal-to-noise+ratio%22">Signal-to-noise ratio</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: The digital voice is multimedia content of great importance, given the range of applications where it can be found. This paper addresses the shortcomings of existing voice authentication algorithms, presenting a completely blind speech authentication and recovery method based on fragile watermarking using the Least Significant Bit (LSB) method. This scheme obtains a compressed version of the original speech signal by Adaptive Differential Pulse Code Modulation (ADPCM) coding and the Discrete-Time Wavelet Transform (DTWT). Authentication bits are then generated by the SHA256 hash function, and the watermark is afterward embedded in the last three LSBs of the original audio samples. Experimental results evaluated on five different audio databases, each comprising speech signals recorded in different situations, contexts, and languages, have demonstrated a high embedding payload and imperceptibility of the watermark, obtaining an average Signal-to-Noise Ratio (SNR) value above 40 d B . Furthermore, the proposed method demonstrates a strong ability to accurately locate and restore up to 50% of a speech signal that has been tampered with, using no additional information. Moreover, the recovered speech signal is intelligible and has an SNR value higher than other recovery schemes, justifying the efficiency of the proposed method. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Multimedia Tools & Applications is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1007/s11042-024-18614-0 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 25 StartPage: 76341 Subjects: – SubjectFull: Adaptive modulation Type: general – SubjectFull: Discrete wavelet transforms Type: general – SubjectFull: Digital watermarking Type: general – SubjectFull: Speech Type: general – SubjectFull: Wavelet transforms Type: general – SubjectFull: Signal-to-noise ratio Type: general Titles: – TitleFull: Speech signal authentication and self-recovery based on DTWT and ADPCM. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Quiñonez-Carbajal, Maria T. – PersonEntity: Name: NameFull: Reyes-Reyes, Rogelio – PersonEntity: Name: NameFull: Ponomaryov, Volodymyr – PersonEntity: Name: NameFull: Cruz-Ramos, Clara – PersonEntity: Name: NameFull: Garcia-Salgado, Beatriz P. IsPartOfRelationships: – BibEntity: Dates: – D: 25 M: 09 Text: Sep2024 Type: published Y: 2024 Identifiers: – Type: issn-print Value: 13807501 Numbering: – Type: volume Value: 83 – Type: issue Value: 31 Titles: – TitleFull: Multimedia Tools & Applications Type: main |
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