000 04142nam a22005415i 4500
001 978-3-031-02563-1
003 DE-He213
005 20240730165037.0
007 cr nn 008mamaa
008 220601s2012 sz | s |||| 0|eng d
020 _a9783031025631
_9978-3-031-02563-1
024 7 _a10.1007/978-3-031-02563-1
_2doi
050 4 _aTK1-9971
072 7 _aTHR
_2bicssc
072 7 _aTEC007000
_2bisacsh
072 7 _aTHR
_2thema
082 0 4 _a621.3
_223
100 1 _aLevinson, Stephen.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_987211
245 1 0 _aArticulatory Speech Synthesis from the Fluid Dynamics of the Vocal Apparatus
_h[electronic resource] /
_cby Stephen Levinson, Don Davis, Scott Slimon, Jun Huang.
250 _a1st ed. 2012.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2012.
300 _aXII, 104 p.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aSynthesis Lectures on Speech and Audio Processing,
_x1932-1678
505 0 _aIntroduction -- Literature Review -- Estimation of Dynamic Articulatory Parameters -- Construction of Articulatory Model Based on MRI Data -- Vocal Fold Excitation Models -- Experimental Results of Articulatory Synthesis -- Conclusion.
520 _aThis book addresses the problem of articulatory speech synthesis based on computed vocal tract geometries and the basic physics of sound production in it. Unlike conventional methods based on analysis/synthesis using the well-known source filter model, which assumes the independence of the excitation and filter, we treat the entire vocal apparatus as one mechanical system that produces sound by means of fluid dynamics. The vocal apparatus is represented as a three-dimensional time-varying mechanism and the sound propagation inside it is due to the non-planar propagation of acoustic waves through a viscous, compressible fluid described by the Navier-Stokes equations. We propose a combined minimum energy and minimum jerk criterion to compute the dynamics of the vocal tract during articulation. Theoretical error bounds and experimental results show that this method obtains a close match to the phonetic target positions while avoiding abrupt changes in the articulatory trajectory. The vocal folds are set into aerodynamic oscillation by the flow of air from the lungs. The modulated air stream then excites the moving vocal tract. This method shows strong evidence for source-filter interaction. Based on our results, we propose that the articulatory speech production model has the potential to synthesize speech and provide a compact parameterization of the speech signal that can be useful in a wide variety of speech signal processing problems. Table of Contents: Introduction / Literature Review / Estimation of Dynamic Articulatory Parameters / Construction of Articulatory Model Based on MRI Data / Vocal Fold Excitation Models / Experimental Results of Articulatory Synthesis / Conclusion.
650 0 _aElectrical engineering.
_987213
650 0 _aSignal processing.
_94052
650 0 _aAcoustical engineering.
_99499
650 1 4 _aElectrical and Electronic Engineering.
_987214
650 2 4 _aSignal, Speech and Image Processing.
_931566
650 2 4 _aEngineering Acoustics.
_931982
700 1 _aDavis, Don.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_987217
700 1 _aSlimon, Scott.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_987219
700 1 _aHuang, Jun.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_987221
710 2 _aSpringerLink (Online service)
_987224
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783031014352
776 0 8 _iPrinted edition:
_z9783031036910
830 0 _aSynthesis Lectures on Speech and Audio Processing,
_x1932-1678
_987225
856 4 0 _uhttps://doi.org/10.1007/978-3-031-02563-1
912 _aZDB-2-SXSC
942 _cEBK
999 _c86067
_d86067