Robust ASR using neural network based speech enhancement and feature simulation
Identifieur interne : 000194 ( Main/Exploration ); précédent : 000193; suivant : 000195Robust ASR using neural network based speech enhancement and feature simulation
Auteurs : Sunit Sivasankaran [France] ; Aditya Arie Nugraha [France] ; Emmanuel Vincent [France] ; Juan Andrés Morales Cordovilla [France] ; Siddharth Dalmia [France] ; Irina Illina [France] ; Antoine Liutkus [France]Source :
English descriptors
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Abstract
We consider the problem of robust automatic speech recog-nition (ASR) in the context of the CHiME-3 Challenge. The proposed system combines three contributions. First, we propose a deep neural network (DNN) based multichannel speech enhancement technique, where the speech and noise spectra are estimated using a DNN based regressor and the spatial parameters are derived in an expectation-maximization(EM) like fashion. Second, a conditional restricted Boltz-mann machine (CRBM) model is trained using the obtained enhanced speech and used to generate simulated training and development datasets. The goal is to increase the similarity between simulated and real data, so as to increase the benefit of multicondition training. Finally, we make some changes to the ASR backend. Our system ranked 4th among 25 entries.
Url:
Affiliations:
- France
- Grand Est, Lorraine (région)
- Metz, Nancy
- Institut national polytechnique de Lorraine, Université Nancy 2, Université de Lorraine
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Le document en format XML
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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>ASR</term><term>CHiME-3</term><term>CRBM</term><term>DNN HMM</term><term>Speech Enhancement</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">We consider the problem of robust automatic speech recog-nition (ASR) in the context of the CHiME-3 Challenge. The proposed system combines three contributions. First, we propose a deep neural network (DNN) based multichannel speech enhancement technique, where the speech and noise spectra are estimated using a DNN based regressor and the spatial parameters are derived in an expectation-maximization(EM) like fashion. Second, a conditional restricted Boltz-mann machine (CRBM) model is trained using the obtained enhanced speech and used to generate simulated training and development datasets. The goal is to increase the similarity between simulated and real data, so as to increase the benefit of multicondition training. Finally, we make some changes to the ASR backend. Our system ranked 4th among 25 entries.</div></front></TEI><affiliations><list><country><li>France</li></country><region><li>Grand Est</li><li>Lorraine (région)</li></region><settlement><li>Metz</li><li>Nancy</li></settlement><orgName><li>Institut national polytechnique de Lorraine</li><li>Université Nancy 2</li><li>Université de Lorraine</li></orgName></list><tree><country name="France"><region name="Grand Est"><name sortKey="Sivasankaran, Sunit" sort="Sivasankaran, Sunit" uniqKey="Sivasankaran S" first="Sunit" last="Sivasankaran">Sunit Sivasankaran</name></region><name sortKey="Dalmia, Siddharth" sort="Dalmia, Siddharth" uniqKey="Dalmia S" first="Siddharth" last="Dalmia">Siddharth Dalmia</name><name sortKey="Illina, Irina" sort="Illina, Irina" uniqKey="Illina I" first="Irina" last="Illina">Irina Illina</name><name sortKey="Liutkus, Antoine" sort="Liutkus, Antoine" uniqKey="Liutkus A" first="Antoine" last="Liutkus">Antoine Liutkus</name><name sortKey="Morales Cordovilla, Juan Andres" sort="Morales Cordovilla, Juan Andres" uniqKey="Morales Cordovilla J" first="Juan Andrés" last="Morales Cordovilla">Juan Andrés Morales Cordovilla</name><name sortKey="Nugraha, Aditya Arie" sort="Nugraha, Aditya Arie" uniqKey="Nugraha A" first="Aditya Arie" last="Nugraha">Aditya Arie Nugraha</name><name sortKey="Vincent, Emmanuel" sort="Vincent, Emmanuel" uniqKey="Vincent E" first="Emmanuel" last="Vincent">Emmanuel Vincent</name></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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|texte= Robust ASR using neural network based speech enhancement and feature simulation
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