Extraction of Temporal Patterns in Multi-rate and Multi-modal Datasets

Antoine Liutkus 1, 2 Umut Şimşekli 3 Taylan Cemgil 3
1 MULTISPEECH - Speech Modeling for Facilitating Oral-Based Communication
Inria Nancy - Grand Est, LORIA - NLPKD - Department of Natural Language Processing & Knowledge Discovery
2 PAROLE - Analysis, perception and recognition of speech
INRIA Lorraine, LORIA - Laboratoire Lorrain de Recherche en Informatique et ses Applications
3 Department of Computer Engineering [Bogazici]
Abstract : We focus on the problem of analyzing corpora composed of irregularly sampled (multi-rate) heterogeneous temporal data. We propose a novel convolutive multi-rate factorization model for extracting multi-modal patterns from such multi-rate data. Our model builds up on previously proposed multi-view (coupled) nonnegative matrix factor-ization techniques, and extends them by accounting for heterogeneous sample rates and enabling the patterns to have a duration. We illustrate the proposed methodology on the joint study of audiovisual data for speech analysis.
Type de document :
Communication dans un congrès
International Conference on Latent Variable Analysis and Signal Separation (LVA/ICA), Aug 2015, Liberec, Czech Republic. 2015
Liste complète des métadonnées

Littérature citée [14 références]  Voir  Masquer  Télécharger
https://hal.inria.fr/hal-01170932
Contributeur : Antoine Liutkus <>
Soumis le : jeudi 2 juillet 2015 - 15:13:09
Dernière modification le : mercredi 21 février 2018 - 07:50:03
Document(s) archivé(s) le : mardi 25 avril 2017 - 23:27:11

Fichier

lva_convolutive_final.pdf
Fichiers produits par l'(les) auteur(s)

Identifiants

  • HAL Id : hal-01170932, version 1

Collections

INRIA | UNIV-LORRAINE | LORIA-NLPKD | LORIA

Citation

Antoine Liutkus, Umut Şimşekli, Taylan Cemgil. Extraction of Temporal Patterns in Multi-rate and Multi-modal Datasets. International Conference on Latent Variable Analysis and Signal Separation (LVA/ICA), Aug 2015, Liberec, Czech Republic. 2015. 〈hal-01170932〉

Exporter

BibTeX TEI DC DCterms EndNote

Partager

Métriques

Consultations de la notice

270

Téléchargements de fichiers

223

Contact


archive-ouverte@inria.fr