Comparison Between Two Spatio-Temporal Organization Maps for Speech Recognition
Identifieur interne : 005520 ( Main/Exploration ); précédent : 005519; suivant : 005521Comparison Between Two Spatio-Temporal Organization Maps for Speech Recognition
Auteurs : Zouhour Neji Ben Salem [Tunisie] ; Laurent Bougrain [France] ; Frédéric Alexandre [France]Source :
- Lecture Notes in Computer Science [ 0302-9743 ]
Abstract
Abstract: In this paper, we compare two models biologically inspired and gathering spatio-temporal data coding, representation and processing. These models are based on Self-Organizing Map (SOM) yielding to a Spatio-Temporel Organization Map (STOM). More precisely, the map is trained using two different spatio-temporal algorithms taking their roots in biological researches: The ST-Kohonen and the Time-Organized Map (TOM). These algorithms use two kinds of spatio-temporal data coding. The first one is based on the domain of complex numbers, while the second is based on the ISI (Inter Spike Interval). STOM is experimented in the field of speech recognition in order to evaluate its performance for such time variable application and to prove that biological models are capable of giving good results as stochastic and hybrid ones.
Url:
DOI: 10.1007/11829898_2
Affiliations:
Links toward previous steps (curation, corpus...)
- to stream Istex, to step Corpus: 003531
- to stream Istex, to step Curation: 003489
- to stream Istex, to step Checkpoint: 001373
- to stream Hal, to step Corpus: 001656
- to stream Hal, to step Curation: 001656
- to stream Hal, to step Checkpoint: 003F53
- to stream Main, to step Merge: 005666
- to stream Main, to step Curation: 005520
Le document en format XML
<record><TEI wicri:istexFullTextTei="biblStruct"><teiHeader><fileDesc><titleStmt><title xml:lang="en">Comparison Between Two Spatio-Temporal Organization Maps for Speech Recognition</title>
<author><name sortKey="Salem, Zouhour Neji Ben" sort="Salem, Zouhour Neji Ben" uniqKey="Salem Z" first="Zouhour Neji Ben" last="Salem">Zouhour Neji Ben Salem</name>
</author>
<author><name sortKey="Bougrain, Laurent" sort="Bougrain, Laurent" uniqKey="Bougrain L" first="Laurent" last="Bougrain">Laurent Bougrain</name>
</author>
<author><name sortKey="Alexandre, Frederic" sort="Alexandre, Frederic" uniqKey="Alexandre F" first="Frédéric" last="Alexandre">Frédéric Alexandre</name>
</author>
</titleStmt>
<publicationStmt><idno type="wicri:source">ISTEX</idno>
<idno type="RBID">ISTEX:DF7E5AE64D2491403C3FB230CD4BED90C64B954E</idno>
<date when="2006" year="2006">2006</date>
<idno type="doi">10.1007/11829898_2</idno>
<idno type="url">https://api.istex.fr/ark:/67375/HCB-81R3763S-G/fulltext.pdf</idno>
<idno type="wicri:Area/Istex/Corpus">003531</idno>
<idno type="wicri:explorRef" wicri:stream="Istex" wicri:step="Corpus" wicri:corpus="ISTEX">003531</idno>
<idno type="wicri:Area/Istex/Curation">003489</idno>
<idno type="wicri:Area/Istex/Checkpoint">001373</idno>
<idno type="wicri:explorRef" wicri:stream="Istex" wicri:step="Checkpoint">001373</idno>
<idno type="wicri:doubleKey">0302-9743:2006:Salem Z:comparison:between:two</idno>
<idno type="wicri:source">HAL</idno>
<idno type="RBID">Hal:inria-00104156</idno>
<idno type="url">https://hal.inria.fr/inria-00104156</idno>
<idno type="wicri:Area/Hal/Corpus">001656</idno>
<idno type="wicri:Area/Hal/Curation">001656</idno>
<idno type="wicri:Area/Hal/Checkpoint">003F53</idno>
<idno type="wicri:explorRef" wicri:stream="Hal" wicri:step="Checkpoint">003F53</idno>
<idno type="wicri:Area/Main/Merge">005666</idno>
<idno type="wicri:Area/Main/Curation">005520</idno>
<idno type="wicri:Area/Main/Exploration">005520</idno>
</publicationStmt>
<sourceDesc><biblStruct><analytic><title level="a" type="main" xml:lang="en">Comparison Between Two Spatio-Temporal Organization Maps for Speech Recognition</title>
<author><name sortKey="Salem, Zouhour Neji Ben" sort="Salem, Zouhour Neji Ben" uniqKey="Salem Z" first="Zouhour Neji Ben" last="Salem">Zouhour Neji Ben Salem</name>
<affiliation wicri:level="1"><country xml:lang="fr">Tunisie</country>
<wicri:regionArea>AI Unit, CRISTAL Laratory, National School of Computer Sciences, Manouba Campus</wicri:regionArea>
<wicri:noRegion>Manouba Campus</wicri:noRegion>
</affiliation>
<affiliation></affiliation>
</author>
<author><name sortKey="Bougrain, Laurent" sort="Bougrain, Laurent" uniqKey="Bougrain L" first="Laurent" last="Bougrain">Laurent Bougrain</name>
<affiliation wicri:level="3"><country xml:lang="fr">France</country>
<wicri:regionArea>Cortex Team, LORIA Laboratory, Nancy</wicri:regionArea>
<placeName><region type="region">Grand Est</region>
<region type="old region">Lorraine (région)</region>
<settlement type="city">Nancy</settlement>
</placeName>
</affiliation>
<affiliation wicri:level="1"><country wicri:rule="url">France</country>
</affiliation>
</author>
<author><name sortKey="Alexandre, Frederic" sort="Alexandre, Frederic" uniqKey="Alexandre F" first="Frédéric" last="Alexandre">Frédéric Alexandre</name>
<affiliation wicri:level="3"><country xml:lang="fr">France</country>
<wicri:regionArea>Cortex Team, LORIA Laboratory, Nancy</wicri:regionArea>
<placeName><region type="region">Grand Est</region>
<region type="old region">Lorraine (région)</region>
<settlement type="city">Nancy</settlement>
</placeName>
</affiliation>
<affiliation wicri:level="1"><country wicri:rule="url">France</country>
</affiliation>
</author>
</analytic>
<monogr></monogr>
<series><title level="s" type="main" xml:lang="en">Lecture Notes in Computer Science</title>
<idno type="ISSN">0302-9743</idno>
<idno type="eISSN">1611-3349</idno>
<idno type="ISSN">0302-9743</idno>
</series>
</biblStruct>
</sourceDesc>
<seriesStmt><idno type="ISSN">0302-9743</idno>
</seriesStmt>
</fileDesc>
<profileDesc><textClass></textClass>
</profileDesc>
</teiHeader>
<front><div type="abstract" xml:lang="en">Abstract: In this paper, we compare two models biologically inspired and gathering spatio-temporal data coding, representation and processing. These models are based on Self-Organizing Map (SOM) yielding to a Spatio-Temporel Organization Map (STOM). More precisely, the map is trained using two different spatio-temporal algorithms taking their roots in biological researches: The ST-Kohonen and the Time-Organized Map (TOM). These algorithms use two kinds of spatio-temporal data coding. The first one is based on the domain of complex numbers, while the second is based on the ISI (Inter Spike Interval). STOM is experimented in the field of speech recognition in order to evaluate its performance for such time variable application and to prove that biological models are capable of giving good results as stochastic and hybrid ones.</div>
</front>
</TEI>
<affiliations><list><country><li>France</li>
<li>Tunisie</li>
</country>
<region><li>Grand Est</li>
<li>Lorraine (région)</li>
</region>
<settlement><li>Nancy</li>
</settlement>
</list>
<tree><country name="Tunisie"><noRegion><name sortKey="Salem, Zouhour Neji Ben" sort="Salem, Zouhour Neji Ben" uniqKey="Salem Z" first="Zouhour Neji Ben" last="Salem">Zouhour Neji Ben Salem</name>
</noRegion>
</country>
<country name="France"><region name="Grand Est"><name sortKey="Bougrain, Laurent" sort="Bougrain, Laurent" uniqKey="Bougrain L" first="Laurent" last="Bougrain">Laurent Bougrain</name>
</region>
<name sortKey="Alexandre, Frederic" sort="Alexandre, Frederic" uniqKey="Alexandre F" first="Frédéric" last="Alexandre">Frédéric Alexandre</name>
<name sortKey="Alexandre, Frederic" sort="Alexandre, Frederic" uniqKey="Alexandre F" first="Frédéric" last="Alexandre">Frédéric Alexandre</name>
<name sortKey="Bougrain, Laurent" sort="Bougrain, Laurent" uniqKey="Bougrain L" first="Laurent" last="Bougrain">Laurent Bougrain</name>
</country>
</tree>
</affiliations>
</record>
Pour manipuler ce document sous Unix (Dilib)
EXPLOR_STEP=$WICRI_ROOT/Wicri/Lorraine/explor/InforLorV4/Data/Main/Exploration
HfdSelect -h $EXPLOR_STEP/biblio.hfd -nk 005520 | SxmlIndent | more
Ou
HfdSelect -h $EXPLOR_AREA/Data/Main/Exploration/biblio.hfd -nk 005520 | SxmlIndent | more
Pour mettre un lien sur cette page dans le réseau Wicri
{{Explor lien |wiki= Wicri/Lorraine |area= InforLorV4 |flux= Main |étape= Exploration |type= RBID |clé= ISTEX:DF7E5AE64D2491403C3FB230CD4BED90C64B954E |texte= Comparison Between Two Spatio-Temporal Organization Maps for Speech Recognition }}
This area was generated with Dilib version V0.6.33. |