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Advance Compression and Watermarking Technique for Speech Signals [electronic resource] / by Rohit Thanki, Komal Borisagar, Surekha Borra.

By: Thanki, Rohit [author.].
Contributor(s): Borisagar, Komal [author.] | Borra, Surekha [author.] | SpringerLink (Online service).
Material type: materialTypeLabelBookSeries: SpringerBriefs in Speech Technology, Studies in Speech Signal Processing, Natural Language Understanding, and Machine Learning: Publisher: Cham : Springer International Publishing : Imprint: Springer, 2018Edition: 1st ed. 2018.Description: XVIII, 69 p. 38 illus., 28 illus. in color. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783319690698.Subject(s): Signal processing | Computational linguistics | Natural language processing (Computer science) | Database management | Signal, Speech and Image Processing | Computational Linguistics | Natural Language Processing (NLP) | Database ManagementAdditional physical formats: Printed edition:: No title; Printed edition:: No titleDDC classification: 621.382 Online resources: Click here to access online
Contents:
Introduction -- Background Information -- Speech Watermarking Technique using Ridgelet, DWT and SVD -- Speech Compression Technique using CS Theory -- Conclusions -- References.
In: Springer Nature eBookSummary: This book introduces methods for copyright protection and compression for speech signals. The first method introduces copyright protection of speech signal using watermarking; the second introduces compression of the speech signal using Compressive Sensing (CS). Both methods are tested and analyzed. The speech watermarking method uses technology such as Finite Ridgelet Transform (FRT), Discrete Wavelet Transform (DWT) and Singular Value Decomposition (SVD). The performance of the method is evaluated and compared with existing watermarking methods. In the speech compression method, the standard Compressive Sensing (CS) process is used for compression of the speech signal. The performance of the proposed method is evaluated using various transform bases like Discrete Fourier Transform (DFT), Discrete Cosine Transform (DCT), Discrete Wavelet Transform (DWT), Singular Value Decomposition (SVD), and Fast Discrete Curvelet Transform (FDCuT).
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Introduction -- Background Information -- Speech Watermarking Technique using Ridgelet, DWT and SVD -- Speech Compression Technique using CS Theory -- Conclusions -- References.

This book introduces methods for copyright protection and compression for speech signals. The first method introduces copyright protection of speech signal using watermarking; the second introduces compression of the speech signal using Compressive Sensing (CS). Both methods are tested and analyzed. The speech watermarking method uses technology such as Finite Ridgelet Transform (FRT), Discrete Wavelet Transform (DWT) and Singular Value Decomposition (SVD). The performance of the method is evaluated and compared with existing watermarking methods. In the speech compression method, the standard Compressive Sensing (CS) process is used for compression of the speech signal. The performance of the proposed method is evaluated using various transform bases like Discrete Fourier Transform (DFT), Discrete Cosine Transform (DCT), Discrete Wavelet Transform (DWT), Singular Value Decomposition (SVD), and Fast Discrete Curvelet Transform (FDCuT).

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