Segmentation Parole/Musique pour la transcription automatique
Identifieur interne : 006D66 ( Main/Exploration ); précédent : 006D65; suivant : 006D67Segmentation Parole/Musique pour la transcription automatique
Auteurs : Joseph Razik [France] ; Dominique Fohr [France] ; Odile Mella [France] ; Nathalie Parlangeau-VallèsSource :
Descripteurs français
- mix :
Abstract
Dans cet article nous présentons une étude sur l'utilisation des paramètres MFCC dans la tâche de segmentation parole/musique indispensable dans les applications de transcription automatique d'émissions radiophoniques. Nous avons étudié, l'influence du nombre de coefficients MFCC, celle des paramètres dynamiques et notamment celui de la variance des coefficients MFCC calculée sur une seconde. Les tests ont été effectués sur un corpus radiophonique réel et difficile et sur le corpus de Scheirer. || The speech/music segmentation process is very useful as a first step for different tasks like speech recognition or automatic transcription. In this article, we present some studies about the use of MFCC for this speech/music segmentation. We mainly use a realworld broadcast corpus with various backgrounds and superimposed segments (speech with music). We investigate the role of the number of cepstral coefficients, the influence of different kinds of dynamic parameters, and the robustness of some of them when a mismatch between train and test conditions occurs. So we can notice that the standard MFCC coefficients with the first and second derivatives achieve good results. But, better performances were obtained with dynamic parameters and mainly with the variance of the static coefficients computed on a longterm window (1s).
Url:
Affiliations:
- France
- Grand Est, Lorraine (région)
- Nancy
- Institut national polytechnique de Lorraine, Université Nancy 2, Université de Lorraine
Links toward previous steps (curation, corpus...)
- to stream Hal, to step Corpus: 006573
- to stream Hal, to step Curation: 006573
- to stream Hal, to step Checkpoint: 004B69
- to stream Main, to step Merge: 007122
- to stream Main, to step Curation: 006D66
Le document en format XML
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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><author><name sortKey="Mella, Odile" sort="Mella, Odile" uniqKey="Mella O" first="Odile" last="Mella">Odile Mella</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 type="url">http://www.inria.fr/equipes/parole</ref></desc><listRelation><relation active="#struct-160" type="direct"></relation><relation name="UMR7503" active="#struct-441569" type="indirect"></relation><relation active="#struct-300009" type="indirect"></relation><relation active="#struct-300291" type="indirect"></relation><relation active="#struct-300292" type="indirect"></relation><relation active="#struct-300293" type="indirect"></relation><relation active="#struct-2496" type="direct"></relation></listRelation><tutelles><tutelle active="#struct-160" type="direct"><org type="laboratory" xml:id="struct-160" status="OLD"><orgName>Laboratoire Lorrain de Recherche en Informatique et ses Applications</orgName><orgName type="acronym">LORIA</orgName><desc><address><addrLine>Campus Scientifique BP 239 54506 Vandoeuvre-lès-Nancy Cedex</addrLine><country key="FR"></country></address><ref type="url">http://www.loria.fr</ref></desc><listRelation><relation name="UMR7503" active="#struct-441569" type="direct"></relation><relation active="#struct-300009" type="direct"></relation><relation active="#struct-300291" type="direct"></relation><relation active="#struct-300292" type="direct"></relation><relation active="#struct-300293" type="direct"></relation></listRelation></org></tutelle><tutelle name="UMR7503" active="#struct-441569" type="indirect"><org type="institution" xml:id="struct-441569" status="VALID"><idno type="ISNI">0000000122597504</idno><idno type="IdRef">02636817X</idno><orgName>Centre National de la Recherche Scientifique</orgName><orgName type="acronym">CNRS</orgName><date type="start">1939-10-19</date><desc><address><country key="FR"></country></address><ref type="url">http://www.cnrs.fr/</ref></desc></org></tutelle><tutelle active="#struct-300009" type="indirect"><org type="institution" xml:id="struct-300009" status="VALID"><orgName>Institut National de Recherche en Informatique et en Automatique</orgName><orgName 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><author><name sortKey="Parlangeau Valles, Nathalie" sort="Parlangeau Valles, Nathalie" uniqKey="Parlangeau Valles N" first="Nathalie" last="Parlangeau-Vallès">Nathalie Parlangeau-Vallès</name></author></analytic></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="mix" xml:lang="fr"><term>automatic transcription</term><term>gmm</term><term>mfcc</term><term>modélisation gmm</term><term>paramétrisation mfcc</term><term>reconnaissance de la parole</term><term>segmentation parole/musique</term><term>speech recognition</term><term>speech/music segmentation</term><term>transcription automatique</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">Dans cet article nous présentons une étude sur l'utilisation des paramètres MFCC dans la tâche de segmentation parole/musique indispensable dans les applications de transcription automatique d'émissions radiophoniques. Nous avons étudié, l'influence du nombre de coefficients MFCC, celle des paramètres dynamiques et notamment celui de la variance des coefficients MFCC calculée sur une seconde. Les tests ont été effectués sur un corpus radiophonique réel et difficile et sur le corpus de Scheirer. || The speech/music segmentation process is very useful as a first step for different tasks like speech recognition or automatic transcription. In this article, we present some studies about the use of MFCC for this speech/music segmentation. We mainly use a realworld broadcast corpus with various backgrounds and superimposed segments (speech with music). We investigate the role of the number of cepstral coefficients, the influence of different kinds of dynamic parameters, and the robustness of some of them when a mismatch between train and test conditions occurs. So we can notice that the standard MFCC coefficients with the first and second derivatives achieve good results. But, better performances were obtained with dynamic parameters and mainly with the variance of the static coefficients computed on a longterm window (1s).</div></front></TEI><affiliations><list><country><li>France</li></country><region><li>Grand Est</li><li>Lorraine (région)</li></region><settlement><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><noCountry><name sortKey="Parlangeau Valles, Nathalie" sort="Parlangeau Valles, Nathalie" uniqKey="Parlangeau Valles N" first="Nathalie" last="Parlangeau-Vallès">Nathalie Parlangeau-Vallès</name></noCountry><country name="France"><region name="Grand Est"><name sortKey="Razik, Joseph" sort="Razik, Joseph" uniqKey="Razik J" first="Joseph" last="Razik">Joseph Razik</name></region><name sortKey="Fohr, Dominique" sort="Fohr, Dominique" uniqKey="Fohr D" first="Dominique" last="Fohr">Dominique Fohr</name><name sortKey="Mella, Odile" sort="Mella, Odile" uniqKey="Mella O" first="Odile" last="Mella">Odile Mella</name></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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