skip to content
Covid-19 virus
COVID-19 Resources

Reliable information about the coronavirus (COVID-19) is available from the World Health Organization (current situation, international travel). Numerous and frequently-updated resource results are available from this WorldCat.org search. OCLC’s WebJunction has pulled together information and resources to assist library staff as they consider how to handle coronavirus issues in their communities.

Image provided by: CDC/ Alissa Eckert, MS; Dan Higgins, MAM
Efficient speaker diarization and low-latency speaker spotting Preview this item
ClosePreview this item
Checking...

Efficient speaker diarization and low-latency speaker spotting

Author: José María Patino VillarNicholas W D EvansMarc DacierEduardo Lleida SolanoSylvain MeignierAll authors
Publisher: 2019.
Dissertation: Thèse de doctorat : Informatique : Sorbonne université : 2019.
Edition/Format:   Computer file : Document : Thesis/dissertation : English
Summary:
La segmentation et le regroupement en locuteurs (SRL) impliquent la détection des locuteurs dans un flux audio et les intervalles pendant lesquels chaque locuteur est actif, c'est-à-dire la détermination de 'qui parle quand'. La première partie des travaux présentés dans cette thèse exploite une approche de modélisation du locuteur utilisant des clés binaires (BKs) comme solution à la SRL. La modélisation
Rating:

(not yet rated) 0 with reviews - Be the first.

Subjects
More like this

Find a copy online

Links to this item

Find a copy in the library

&AllPage.SpinnerRetrieving; Finding libraries that hold this item...

Details

Genre/Form: Thèses et écrits académiques
Material Type: Document, Thesis/dissertation, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: José María Patino Villar; Nicholas W D Evans; Marc Dacier; Eduardo Lleida Solano; Sylvain Meignier; Isabel Trancoso; Sorbonne université (Paris / 2018-....).; École doctorale Informatique, télécommunications et électronique de Paris.; Institut EURECOM (Sophia-Antipolis, Alpes-Maritimes).
OCLC Number: 1150886197
Notes: Titre provenant de l'écran-titre.
Description: 1 online resource
Responsibility: José María Patino Villar ; sous la direction de Nicholas W. D. Evans.

Abstract:

La segmentation et le regroupement en locuteurs (SRL) impliquent la détection des locuteurs dans un flux audio et les intervalles pendant lesquels chaque locuteur est actif, c'est-à-dire la détermination de 'qui parle quand'. La première partie des travaux présentés dans cette thèse exploite une approche de modélisation du locuteur utilisant des clés binaires (BKs) comme solution à la SRL. La modélisation BK est efficace et fonctionne sans données d'entraînement externes, car elle utilise uniquement des données de test. Les contributions présentées incluent l'extraction des BKs basée sur l'analyse spectrale multi-résolution, la détection explicite des changements de locuteurs utilisant les BKs, ainsi que les techniques de fusion SRL qui combinent les avantages des BKs et des solutions basées sur un apprentissage approfondi. La tâche de la SRL est étroitement liée à celle de la reconnaissance ou de la détection du locuteur, qui consiste à comparer deux segments de parole et à déterminer s'ils ont été prononcés par le même locuteur ou non. Même si de nombreuses applications pratiques nécessitent leur combinaison, les deux tâches sont traditionnellement exécutées indépendamment l'une de l'autre. La deuxième partie de cette thèse porte sur une application où les solutions de SRL et de reconnaissance des locuteurs sont réunies. La nouvelle tâche, appelée détection de locuteurs à faible latence, consiste à détecter rapidement les locuteurs connus dans des flux audio à locuteurs multiples. Il s'agit de repenser la SRL en ligne et la manière dont les sous-systèmes de SRL et de détection devraient être combinés au mieux.

Speaker diarization (SD) involves the detection of speakers within an audio stream and the intervals during which each speaker is active, i.e. the determination of 'who spoken when'. The first part of the work presented in this thesis exploits an approach to speaker modelling involving binary keys (BKs) as a solution to SD. BK modelling is efficient and operates without external training data, as it operates using test data alone. The presented contributions include the extraction of BKs based on multi-resolution spectral analysis, the explicit detection of speaker changes using BKs, as well as SD fusion techniques that combine the benefits of both BK and deep learning based solutions. The SD task is closely linked to that of speaker recognition or detection, which involves the comparison of two speech segments and the determination of whether or not they were uttered by the same speaker. Even if many practical applications require their combination, the two tasks are traditionally tackled independently from each other. The second part of this thesis considers an application where SD and speaker recognition solutions are brought together. The new task, coined low latency speaker spotting (LLSS), involves the rapid detection of known speakers within multi-speaker audio streams. It involves the re-thinking of online diarization and the manner by which diarization and detection sub-systems should best be combined.

Reviews

User-contributed reviews
Retrieving GoodReads reviews...
Retrieving DOGObooks reviews...

Tags

Be the first.
Confirm this request

You may have already requested this item. Please select Ok if you would like to proceed with this request anyway.

Linked Data


\n\n

Primary Entity<\/h3>\n
<http:\/\/www.worldcat.org\/oclc\/1150886197<\/a>> # Efficient speaker diarization and low-latency speaker spotting<\/span>\n\u00A0\u00A0\u00A0\u00A0a \nschema:MediaObject<\/a>, bgn:ComputerFile<\/a>, schema:CreativeWork<\/a>, bgn:Thesis<\/a> ;\u00A0\u00A0\u00A0\nbgn:inSupportOf<\/a> \"Th\u00E8se de doctorat : Informatique : Sorbonne universit\u00E9 : 2019.<\/span>\" ;\u00A0\u00A0\u00A0\nlibrary:oclcnum<\/a> \"1150886197<\/span>\" ;\u00A0\u00A0\u00A0\nlibrary:placeOfPublication<\/a> <http:\/\/id.loc.gov\/vocabulary\/countries\/fr<\/a>> ;\u00A0\u00A0\u00A0\nschema:about<\/a> <http:\/\/experiment.worldcat.org\/entity\/work\/data\/10167900581#Topic\/identification_biometrique<\/a>> ; # Identification biom\u00E9trique<\/span>\n\u00A0\u00A0\u00A0\nschema:about<\/a> <http:\/\/experiment.worldcat.org\/entity\/work\/data\/10167900581#Thing\/segmentation_et_regroupement_en_locuteur<\/a>> ; # Segmentation et regroupement en locuteur<\/span>\n\u00A0\u00A0\u00A0\nschema:about<\/a> <http:\/\/experiment.worldcat.org\/entity\/work\/data\/10167900581#Thing\/biometrie_vocale<\/a>> ; # Biom\u00E9trie vocale<\/span>\n\u00A0\u00A0\u00A0\nschema:about<\/a> <http:\/\/experiment.worldcat.org\/entity\/work\/data\/10167900581#Thing\/faible_latence<\/a>> ; # Faible latence<\/span>\n\u00A0\u00A0\u00A0\nschema:about<\/a> <http:\/\/dewey.info\/class\/006.248\/<\/a>> ;\u00A0\u00A0\u00A0\nschema:about<\/a> <http:\/\/experiment.worldcat.org\/entity\/work\/data\/10167900581#Thing\/apprentissage_automatique<\/a>> ; # Apprentissage automatique<\/span>\n\u00A0\u00A0\u00A0\nschema:about<\/a> <http:\/\/experiment.worldcat.org\/entity\/work\/data\/10167900581#Topic\/traitement_automatique_de_la_parole<\/a>> ; # Traitement automatique de la parole<\/span>\n\u00A0\u00A0\u00A0\nschema:about<\/a> <http:\/\/experiment.worldcat.org\/entity\/work\/data\/10167900581#Thing\/reconnaissance_automatique_du_locuteur<\/a>> ; # Reconnaissance automatique du locuteur<\/span>\n\u00A0\u00A0\u00A0\nschema:about<\/a> <http:\/\/experiment.worldcat.org\/entity\/work\/data\/10167900581#Thing\/apprentissage_profond<\/a>> ; # Apprentissage profond<\/span>\n\u00A0\u00A0\u00A0\nschema:about<\/a> <http:\/\/experiment.worldcat.org\/entity\/work\/data\/10167900581#Topic\/identification_automatique<\/a>> ; # Identification automatique<\/span>\n\u00A0\u00A0\u00A0\nschema:author<\/a> <http:\/\/experiment.worldcat.org\/entity\/work\/data\/10167900581#Person\/patino_villar_jose_maria_1991<\/a>> ; # Jos\u00E9 Mar\u00EDa Patino Villar<\/span>\n\u00A0\u00A0\u00A0\nschema:contributor<\/a> <http:\/\/experiment.worldcat.org\/entity\/work\/data\/10167900581#Organization\/ecole_doctorale_informatique_telecommunications_et_electronique_de_paris<\/a>> ; # \u00C9cole doctorale Informatique, t\u00E9l\u00E9communications et \u00E9lectronique de Paris.<\/span>\n\u00A0\u00A0\u00A0\nschema:contributor<\/a> <http:\/\/experiment.worldcat.org\/entity\/work\/data\/10167900581#Person\/lleida_solano_eduardo<\/a>> ; # Eduardo Lleida Solano<\/span>\n\u00A0\u00A0\u00A0\nschema:contributor<\/a> <http:\/\/experiment.worldcat.org\/entity\/work\/data\/10167900581#Person\/evans_nicholas_w_d_19<\/a>> ; # Nicholas W. D. Evans<\/span>\n\u00A0\u00A0\u00A0\nschema:contributor<\/a> <http:\/\/experiment.worldcat.org\/entity\/work\/data\/10167900581#Organization\/institut_eurecom_sophia_antipolis_alpes_maritimes<\/a>> ; # Institut EURECOM (Sophia-Antipolis, Alpes-Maritimes).<\/span>\n\u00A0\u00A0\u00A0\nschema:contributor<\/a> <http:\/\/experiment.worldcat.org\/entity\/work\/data\/10167900581#Person\/trancoso_isabel<\/a>> ; # Isabel Trancoso<\/span>\n\u00A0\u00A0\u00A0\nschema:contributor<\/a> <http:\/\/experiment.worldcat.org\/entity\/work\/data\/10167900581#Organization\/sorbonne_universite_paris_2018<\/a>> ; # Sorbonne universit\u00E9 (Paris \/ 2018-....).<\/span>\n\u00A0\u00A0\u00A0\nschema:contributor<\/a> <http:\/\/experiment.worldcat.org\/entity\/work\/data\/10167900581#Person\/meignier_sylvain<\/a>> ; # Sylvain Meignier<\/span>\n\u00A0\u00A0\u00A0\nschema:contributor<\/a> <http:\/\/experiment.worldcat.org\/entity\/work\/data\/10167900581#Person\/dacier_marc_1965<\/a>> ; # Marc Dacier<\/span>\n\u00A0\u00A0\u00A0\nschema:datePublished<\/a> \"2019<\/span>\" ;\u00A0\u00A0\u00A0\nschema:description<\/a> \"Speaker diarization (SD) involves the detection of speakers within an audio stream and the intervals during which each speaker is active, i.e. the determination of \'who spoken when\'. The first part of the work presented in this thesis exploits an approach to speaker modelling involving binary keys (BKs) as a solution to SD. BK modelling is efficient and operates without external training data, as it operates using test data alone. The presented contributions include the extraction of BKs based on multi-resolution spectral analysis, the explicit detection of speaker changes using BKs, as well as SD fusion techniques that combine the benefits of both BK and deep learning based solutions. The SD task is closely linked to that of speaker recognition or detection, which involves the comparison of two speech segments and the determination of whether or not they were uttered by the same speaker. Even if many practical applications require their combination, the two tasks are traditionally tackled independently from each other. The second part of this thesis considers an application where SD and speaker recognition solutions are brought together. The new task, coined low latency speaker spotting (LLSS), involves the rapid detection of known speakers within multi-speaker audio streams. It involves the re-thinking of online diarization and the manner by which diarization and detection sub-systems should best be combined.<\/span>\" ;\u00A0\u00A0\u00A0\nschema:description<\/a> \"La segmentation et le regroupement en locuteurs (SRL) impliquent la d\u00E9tection des locuteurs dans un flux audio et les intervalles pendant lesquels chaque locuteur est actif, c\'est-\u00E0-dire la d\u00E9termination de \'qui parle quand\'. La premi\u00E8re partie des travaux pr\u00E9sent\u00E9s dans cette th\u00E8se exploite une approche de mod\u00E9lisation du locuteur utilisant des cl\u00E9s binaires (BKs) comme solution \u00E0 la SRL. La mod\u00E9lisation BK est efficace et fonctionne sans donn\u00E9es d\'entra\u00EEnement externes, car elle utilise uniquement des donn\u00E9es de test. Les contributions pr\u00E9sent\u00E9es incluent l\'extraction des BKs bas\u00E9e sur l\'analyse spectrale multi-r\u00E9solution, la d\u00E9tection explicite des changements de locuteurs utilisant les BKs, ainsi que les techniques de fusion SRL qui combinent les avantages des BKs et des solutions bas\u00E9es sur un apprentissage approfondi. La t\u00E2che de la SRL est \u00E9troitement li\u00E9e \u00E0 celle de la reconnaissance ou de la d\u00E9tection du locuteur, qui consiste \u00E0 comparer deux segments de parole et \u00E0 d\u00E9terminer s\'ils ont \u00E9t\u00E9 prononc\u00E9s par le m\u00EAme locuteur ou non. M\u00EAme si de nombreuses applications pratiques n\u00E9cessitent leur combinaison, les deux t\u00E2ches sont traditionnellement ex\u00E9cut\u00E9es ind\u00E9pendamment l\'une de l\'autre. La deuxi\u00E8me partie de cette th\u00E8se porte sur une application o\u00F9 les solutions de SRL et de reconnaissance des locuteurs sont r\u00E9unies. La nouvelle t\u00E2che, appel\u00E9e d\u00E9tection de locuteurs \u00E0 faible latence, consiste \u00E0 d\u00E9tecter rapidement les locuteurs connus dans des flux audio \u00E0 locuteurs multiples. Il s\'agit de repenser la SRL en ligne et la mani\u00E8re dont les sous-syst\u00E8mes de SRL et de d\u00E9tection devraient \u00EAtre combin\u00E9s au mieux.<\/span>\" ;\u00A0\u00A0\u00A0\nschema:exampleOfWork<\/a> <http:\/\/worldcat.org\/entity\/work\/id\/10167900581<\/a>> ;\u00A0\u00A0\u00A0\nschema:genre<\/a> \"Th\u00E8ses et \u00E9crits acad\u00E9miques<\/span>\" ;\u00A0\u00A0\u00A0\nschema:inLanguage<\/a> \"en<\/span>\" ;\u00A0\u00A0\u00A0\nschema:name<\/a> \"Efficient speaker diarization and low-latency speaker spotting<\/span>\" ;\u00A0\u00A0\u00A0\nschema:productID<\/a> \"1150886197<\/span>\" ;\u00A0\u00A0\u00A0\nschema:url<\/a> <http:\/\/www.theses.fr\/2019SORUS003\/document<\/a>> ;\u00A0\u00A0\u00A0\nschema:url<\/a> <http:\/\/www.theses.fr\/2019SORUS003\/abes<\/a>> ;\u00A0\u00A0\u00A0\nschema:url<\/a> <https:\/\/tel.archives-ouvertes.fr\/tel-02458517<\/a>> ;\u00A0\u00A0\u00A0\nwdrs:describedby<\/a> <http:\/\/www.worldcat.org\/title\/-\/oclc\/1150886197<\/a>> ;\u00A0\u00A0\u00A0\u00A0.\n\n\n<\/div>\n\n

Related Entities<\/h3>\n
<http:\/\/dewey.info\/class\/006.248\/<\/a>>\u00A0\u00A0\u00A0\u00A0a \nschema:Intangible<\/a> ;\u00A0\u00A0\u00A0\u00A0.\n\n\n<\/div>\n
<http:\/\/experiment.worldcat.org\/entity\/work\/data\/10167900581#Organization\/ecole_doctorale_informatique_telecommunications_et_electronique_de_paris<\/a>> # \u00C9cole doctorale Informatique, t\u00E9l\u00E9communications et \u00E9lectronique de Paris.<\/span>\n\u00A0\u00A0\u00A0\u00A0a \nschema:Organization<\/a> ;\u00A0\u00A0\u00A0\nschema:name<\/a> \"\u00C9cole doctorale Informatique, t\u00E9l\u00E9communications et \u00E9lectronique de Paris.<\/span>\" ;\u00A0\u00A0\u00A0\u00A0.\n\n\n<\/div>\n
<http:\/\/experiment.worldcat.org\/entity\/work\/data\/10167900581#Organization\/institut_eurecom_sophia_antipolis_alpes_maritimes<\/a>> # Institut EURECOM (Sophia-Antipolis, Alpes-Maritimes).<\/span>\n\u00A0\u00A0\u00A0\u00A0a \nschema:Organization<\/a> ;\u00A0\u00A0\u00A0\nschema:name<\/a> \"Institut EURECOM (Sophia-Antipolis, Alpes-Maritimes).<\/span>\" ;\u00A0\u00A0\u00A0\u00A0.\n\n\n<\/div>\n
<http:\/\/experiment.worldcat.org\/entity\/work\/data\/10167900581#Organization\/sorbonne_universite_paris_2018<\/a>> # Sorbonne universit\u00E9 (Paris \/ 2018-....).<\/span>\n\u00A0\u00A0\u00A0\u00A0a \nschema:Organization<\/a> ;\u00A0\u00A0\u00A0\nschema:name<\/a> \"Sorbonne universit\u00E9 (Paris \/ 2018-....).<\/span>\" ;\u00A0\u00A0\u00A0\u00A0.\n\n\n<\/div>\n
<http:\/\/experiment.worldcat.org\/entity\/work\/data\/10167900581#Person\/dacier_marc_1965<\/a>> # Marc Dacier<\/span>\n\u00A0\u00A0\u00A0\u00A0a \nschema:Person<\/a> ;\u00A0\u00A0\u00A0\nschema:birthDate<\/a> \"1965<\/span>\" ;\u00A0\u00A0\u00A0\nschema:deathDate<\/a> \"\" ;\u00A0\u00A0\u00A0\nschema:familyName<\/a> \"Dacier<\/span>\" ;\u00A0\u00A0\u00A0\nschema:givenName<\/a> \"Marc<\/span>\" ;\u00A0\u00A0\u00A0\nschema:name<\/a> \"Marc Dacier<\/span>\" ;\u00A0\u00A0\u00A0\u00A0.\n\n\n<\/div>\n
<http:\/\/experiment.worldcat.org\/entity\/work\/data\/10167900581#Person\/evans_nicholas_w_d_19<\/a>> # Nicholas W. D. Evans<\/span>\n\u00A0\u00A0\u00A0\u00A0a \nschema:Person<\/a> ;\u00A0\u00A0\u00A0\nschema:birthDate<\/a> \"19..<\/span>\" ;\u00A0\u00A0\u00A0\nschema:deathDate<\/a> \"\" ;\u00A0\u00A0\u00A0\nschema:familyName<\/a> \"Evans<\/span>\" ;\u00A0\u00A0\u00A0\nschema:givenName<\/a> \"Nicholas W. D.<\/span>\" ;\u00A0\u00A0\u00A0\nschema:name<\/a> \"Nicholas W. D. Evans<\/span>\" ;\u00A0\u00A0\u00A0\u00A0.\n\n\n<\/div>\n
<http:\/\/experiment.worldcat.org\/entity\/work\/data\/10167900581#Person\/lleida_solano_eduardo<\/a>> # Eduardo Lleida Solano<\/span>\n\u00A0\u00A0\u00A0\u00A0a \nschema:Person<\/a> ;\u00A0\u00A0\u00A0\nschema:familyName<\/a> \"Lleida Solano<\/span>\" ;\u00A0\u00A0\u00A0\nschema:givenName<\/a> \"Eduardo<\/span>\" ;\u00A0\u00A0\u00A0\nschema:name<\/a> \"Eduardo Lleida Solano<\/span>\" ;\u00A0\u00A0\u00A0\u00A0.\n\n\n<\/div>\n
<http:\/\/experiment.worldcat.org\/entity\/work\/data\/10167900581#Person\/meignier_sylvain<\/a>> # Sylvain Meignier<\/span>\n\u00A0\u00A0\u00A0\u00A0a \nschema:Person<\/a> ;\u00A0\u00A0\u00A0\nschema:familyName<\/a> \"Meignier<\/span>\" ;\u00A0\u00A0\u00A0\nschema:givenName<\/a> \"Sylvain<\/span>\" ;\u00A0\u00A0\u00A0\nschema:name<\/a> \"Sylvain Meignier<\/span>\" ;\u00A0\u00A0\u00A0\u00A0.\n\n\n<\/div>\n
<http:\/\/experiment.worldcat.org\/entity\/work\/data\/10167900581#Person\/patino_villar_jose_maria_1991<\/a>> # Jos\u00E9 Mar\u00EDa Patino Villar<\/span>\n\u00A0\u00A0\u00A0\u00A0a \nschema:Person<\/a> ;\u00A0\u00A0\u00A0\nschema:birthDate<\/a> \"1991<\/span>\" ;\u00A0\u00A0\u00A0\nschema:deathDate<\/a> \"\" ;\u00A0\u00A0\u00A0\nschema:familyName<\/a> \"Patino Villar<\/span>\" ;\u00A0\u00A0\u00A0\nschema:givenName<\/a> \"Jos\u00E9 Mar\u00EDa<\/span>\" ;\u00A0\u00A0\u00A0\nschema:name<\/a> \"Jos\u00E9 Mar\u00EDa Patino Villar<\/span>\" ;\u00A0\u00A0\u00A0\u00A0.\n\n\n<\/div>\n
<http:\/\/experiment.worldcat.org\/entity\/work\/data\/10167900581#Person\/trancoso_isabel<\/a>> # Isabel Trancoso<\/span>\n\u00A0\u00A0\u00A0\u00A0a \nschema:Person<\/a> ;\u00A0\u00A0\u00A0\nschema:familyName<\/a> \"Trancoso<\/span>\" ;\u00A0\u00A0\u00A0\nschema:givenName<\/a> \"Isabel<\/span>\" ;\u00A0\u00A0\u00A0\nschema:name<\/a> \"Isabel Trancoso<\/span>\" ;\u00A0\u00A0\u00A0\u00A0.\n\n\n<\/div>\n
<http:\/\/experiment.worldcat.org\/entity\/work\/data\/10167900581#Thing\/apprentissage_automatique<\/a>> # Apprentissage automatique<\/span>\n\u00A0\u00A0\u00A0\u00A0a \nschema:Thing<\/a> ;\u00A0\u00A0\u00A0\nschema:name<\/a> \"Apprentissage automatique<\/span>\" ;\u00A0\u00A0\u00A0\u00A0.\n\n\n<\/div>\n
<http:\/\/experiment.worldcat.org\/entity\/work\/data\/10167900581#Thing\/apprentissage_profond<\/a>> # Apprentissage profond<\/span>\n\u00A0\u00A0\u00A0\u00A0a \nschema:Thing<\/a> ;\u00A0\u00A0\u00A0\nschema:name<\/a> \"Apprentissage profond<\/span>\" ;\u00A0\u00A0\u00A0\u00A0.\n\n\n<\/div>\n
<http:\/\/experiment.worldcat.org\/entity\/work\/data\/10167900581#Thing\/biometrie_vocale<\/a>> # Biom\u00E9trie vocale<\/span>\n\u00A0\u00A0\u00A0\u00A0a \nschema:Thing<\/a> ;\u00A0\u00A0\u00A0\nschema:name<\/a> \"Biom\u00E9trie vocale<\/span>\" ;\u00A0\u00A0\u00A0\u00A0.\n\n\n<\/div>\n
<http:\/\/experiment.worldcat.org\/entity\/work\/data\/10167900581#Thing\/faible_latence<\/a>> # Faible latence<\/span>\n\u00A0\u00A0\u00A0\u00A0a \nschema:Thing<\/a> ;\u00A0\u00A0\u00A0\nschema:name<\/a> \"Faible latence<\/span>\" ;\u00A0\u00A0\u00A0\u00A0.\n\n\n<\/div>\n
<http:\/\/experiment.worldcat.org\/entity\/work\/data\/10167900581#Thing\/reconnaissance_automatique_du_locuteur<\/a>> # Reconnaissance automatique du locuteur<\/span>\n\u00A0\u00A0\u00A0\u00A0a \nschema:Thing<\/a> ;\u00A0\u00A0\u00A0\nschema:name<\/a> \"Reconnaissance automatique du locuteur<\/span>\" ;\u00A0\u00A0\u00A0\u00A0.\n\n\n<\/div>\n
<http:\/\/experiment.worldcat.org\/entity\/work\/data\/10167900581#Thing\/segmentation_et_regroupement_en_locuteur<\/a>> # Segmentation et regroupement en locuteur<\/span>\n\u00A0\u00A0\u00A0\u00A0a \nschema:Thing<\/a> ;\u00A0\u00A0\u00A0\nschema:name<\/a> \"Segmentation et regroupement en locuteur<\/span>\" ;\u00A0\u00A0\u00A0\u00A0.\n\n\n<\/div>\n
<http:\/\/experiment.worldcat.org\/entity\/work\/data\/10167900581#Topic\/identification_automatique<\/a>> # Identification automatique<\/span>\n\u00A0\u00A0\u00A0\u00A0a \nschema:Intangible<\/a> ;\u00A0\u00A0\u00A0\nschema:name<\/a> \"Identification automatique<\/span>\" ;\u00A0\u00A0\u00A0\u00A0.\n\n\n<\/div>\n
<http:\/\/experiment.worldcat.org\/entity\/work\/data\/10167900581#Topic\/identification_biometrique<\/a>> # Identification biom\u00E9trique<\/span>\n\u00A0\u00A0\u00A0\u00A0a \nschema:Intangible<\/a> ;\u00A0\u00A0\u00A0\nschema:name<\/a> \"Identification biom\u00E9trique<\/span>\" ;\u00A0\u00A0\u00A0\u00A0.\n\n\n<\/div>\n
<http:\/\/experiment.worldcat.org\/entity\/work\/data\/10167900581#Topic\/traitement_automatique_de_la_parole<\/a>> # Traitement automatique de la parole<\/span>\n\u00A0\u00A0\u00A0\u00A0a \nschema:Intangible<\/a> ;\u00A0\u00A0\u00A0\nschema:name<\/a> \"Traitement automatique de la parole<\/span>\" ;\u00A0\u00A0\u00A0\u00A0.\n\n\n<\/div>\n
<http:\/\/id.loc.gov\/vocabulary\/countries\/fr<\/a>>\u00A0\u00A0\u00A0\u00A0a \nschema:Place<\/a> ;\u00A0\u00A0\u00A0\ndcterms:identifier<\/a> \"fr<\/span>\" ;\u00A0\u00A0\u00A0\u00A0.\n\n\n<\/div>\n
<http:\/\/www.theses.fr\/2019SORUS003\/document<\/a>>\u00A0\u00A0\u00A0\nrdfs:comment<\/a> \"Acc\u00E8s au texte int\u00E9gral<\/span>\" ;\u00A0\u00A0\u00A0\u00A0.\n\n\n<\/div>\n