An Effective Lip Tracking Algorithm for Acoustic-to-Articulatory Inversion
Identifieur interne : 006998 ( Main/Merge ); précédent : 006997; suivant : 006999An Effective Lip Tracking Algorithm for Acoustic-to-Articulatory Inversion
Auteurs : Jingying Chen [France] ; Marie-Odile Berger [France] ; Yves Laprie [France]Source :
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Abstract
Although automatic speech recognition systems can now perform well under certain conditions, they still don't provide good results in real life conditions, especially in noisy environments. Several authors have suggested that using articulatory features rather than acoustic features as a basis for speech parameterization would help yield better recognition results. The articulatory features can be recovered from the speech signal by acoustic-to-articulatory inversion. Given the acoustic signal, the recovery of the articulatory state is considered difficult. The reason is the "one-to-many" nature of the acoustic-toarticulatory inversion problem: a given articulatory state has always only one acoustic realization but an acoustic signal can be the outcome of more than one articulatory states. Since visual information is complementary to acoustic information in the inversion, lip tracking is proposed in this paper to provide visual information of lip movement for the acoustic-to-articulatory inversion. Encouraging results have proven the effectiveness of this method which provides useful information (i.e. mouth width and height) for inversion.
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region" nuts="2">Lorraine (région)</region></placeName><orgName type="university">Université Nancy 2</orgName><orgName type="institution" wicri:auto="newGroup">Université de Lorraine</orgName><placeName><settlement type="city">Nancy</settlement><region type="region" nuts="2">Grand Est</region><region type="old region" nuts="2">Lorraine (région)</region></placeName><orgName type="university">Institut national polytechnique de Lorraine</orgName><orgName type="institution" wicri:auto="newGroup">Université de Lorraine</orgName></affiliation></author><author><name sortKey="Laprie, Yves" sort="Laprie, Yves" uniqKey="Laprie Y" first="Yves" last="Laprie">Yves Laprie</name><affiliation wicri:level="1"><hal:affiliation type="researchteam" xml:id="struct-2359" status="OLD"><idno type="RNSR">200118295L</idno><orgName>Analysis, perception and recognition of speech</orgName><orgName type="acronym">PAROLE</orgName><desc><address><country key="FR"></country></address><ref 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type="acronym">Inria</orgName><desc><address><addrLine>Domaine de VoluceauRocquencourt - BP 10578153 Le Chesnay Cedex</addrLine><country key="FR"></country></address><ref type="url">http://www.inria.fr/en/</ref></desc></org></tutelle><tutelle active="#struct-300291" type="indirect"><org type="institution" xml:id="struct-300291" status="OLD"><orgName>Université Henri Poincaré - Nancy 1</orgName><orgName type="acronym">UHP</orgName><date type="end">2011-12-31</date><desc><address><addrLine>24-30 rue Lionnois, BP 60120, 54 003 NANCY cedex, France</addrLine><country key="FR"></country></address></desc></org></tutelle><tutelle active="#struct-300292" type="indirect"><org type="institution" xml:id="struct-300292" status="OLD"><orgName>Université Nancy 2</orgName><date type="end">2011-12-31</date><desc><address><addrLine>91 avenue de la Libération, BP 454, 54001 Nancy cedex</addrLine><country key="FR"></country></address></desc></org></tutelle><tutelle active="#struct-300293" type="indirect"><org type="institution" xml:id="struct-300293" status="OLD"><orgName>Institut National Polytechnique de Lorraine</orgName><orgName type="acronym">INPL</orgName><date type="end">2011-12-31</date><desc><address><country key="FR"></country></address></desc></org></tutelle><tutelle active="#struct-2496" type="direct"><org type="laboratory" xml:id="struct-2496" status="OLD"><orgName>INRIA Lorraine</orgName><desc><address><addrLine>615 rue du Jardin Botanique 54600 Villers-lès-Nancy</addrLine><country key="FR"></country></address><ref type="url">http://www.inria.fr/centre-de-recherche-inria/nancy-grand-est</ref></desc><listRelation><relation active="#struct-300009" type="direct"></relation></listRelation></org></tutelle></tutelles></hal:affiliation><country>France</country><placeName><settlement type="city">Nancy</settlement><region type="region" nuts="2">Grand Est</region><region type="old region" nuts="2">Lorraine (région)</region></placeName><orgName type="university">Université Nancy 2</orgName><orgName type="institution" wicri:auto="newGroup">Université de Lorraine</orgName><placeName><settlement type="city">Nancy</settlement><region type="region" nuts="2">Grand Est</region><region type="old region" nuts="2">Lorraine (région)</region></placeName><orgName type="university">Institut national polytechnique de Lorraine</orgName><orgName type="institution" wicri:auto="newGroup">Université de Lorraine</orgName></affiliation></author></analytic></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="mix" xml:lang="en"><term>image</term><term>image processing</term><term>lip tracking</term><term>lop tracking</term><term>parole</term><term>speech processing</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">Although automatic speech recognition systems can now perform well under certain conditions, they still don't provide good results in real life conditions, especially in noisy environments. Several authors have suggested that using articulatory features rather than acoustic features as a basis for speech parameterization would help yield better recognition results. The articulatory features can be recovered from the speech signal by acoustic-to-articulatory inversion. Given the acoustic signal, the recovery of the articulatory state is considered difficult. The reason is the "one-to-many" nature of the acoustic-toarticulatory inversion problem: a given articulatory state has always only one acoustic realization but an acoustic signal can be the outcome of more than one articulatory states. Since visual information is complementary to acoustic information in the inversion, lip tracking is proposed in this paper to provide visual information of lip movement for the acoustic-to-articulatory inversion. Encouraging results have proven the effectiveness of this method which provides useful information (i.e. mouth width and height) for inversion.</div></front></TEI></record>Pour manipuler ce document sous Unix (Dilib)
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