000 03692nam a22006015i 4500
001 978-3-319-69069-8
003 DE-He213
005 20220801221624.0
007 cr nn 008mamaa
008 171103s2018 sz | s |||| 0|eng d
020 _a9783319690698
_9978-3-319-69069-8
024 7 _a10.1007/978-3-319-69069-8
_2doi
050 4 _aTK5102.9
072 7 _aTJF
_2bicssc
072 7 _aUYS
_2bicssc
072 7 _aTEC008000
_2bisacsh
072 7 _aTJF
_2thema
072 7 _aUYS
_2thema
082 0 4 _a621.382
_223
100 1 _aThanki, Rohit.
_eauthor.
_0(orcid)0000-0002-0645-6266
_1https://orcid.org/0000-0002-0645-6266
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_957064
245 1 0 _aAdvance Compression and Watermarking Technique for Speech Signals
_h[electronic resource] /
_cby Rohit Thanki, Komal Borisagar, Surekha Borra.
250 _a1st ed. 2018.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2018.
300 _aXVIII, 69 p. 38 illus., 28 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aSpringerBriefs in Speech Technology, Studies in Speech Signal Processing, Natural Language Understanding, and Machine Learning,
_x2191-7388
505 0 _aIntroduction -- Background Information -- Speech Watermarking Technique using Ridgelet, DWT and SVD -- Speech Compression Technique using CS Theory -- Conclusions -- References.
520 _aThis 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).
650 0 _aSignal processing.
_94052
650 0 _aComputational linguistics.
_96146
650 0 _aNatural language processing (Computer science).
_94741
650 0 _aDatabase management.
_93157
650 1 4 _aSignal, Speech and Image Processing .
_931566
650 2 4 _aComputational Linguistics.
_96146
650 2 4 _aNatural Language Processing (NLP).
_931587
650 2 4 _aDatabase Management.
_93157
700 1 _aBorisagar, Komal.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_957065
700 1 _aBorra, Surekha.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_918089
710 2 _aSpringerLink (Online service)
_957066
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783319690681
776 0 8 _iPrinted edition:
_z9783319690704
830 0 _aSpringerBriefs in Speech Technology, Studies in Speech Signal Processing, Natural Language Understanding, and Machine Learning,
_x2191-7388
_957067
856 4 0 _uhttps://doi.org/10.1007/978-3-319-69069-8
912 _aZDB-2-ENG
912 _aZDB-2-SXE
942 _cEBK
999 _c79868
_d79868