Unsupervised Word Segmentation from Speech ...
Document type :
Communication dans un congrès avec actes
Title :
Unsupervised Word Segmentation from Speech with Attention
Author(s) :
Godard, Pierre [Auteur]
Traitement du Langage Parlé [TLP]
Zanon Boito, Marcely [Auteur]
Laboratoire d'Informatique de Grenoble [LIG ]
Ondel, Lucas [Auteur]
Brno University of Technology [Brno] [BUT]
Berard, Alexandre [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Yvon, François [Auteur]
Traitement du Langage Parlé [TLP]
Villavicencio, Aline [Auteur]
School of Computer Science and Electronic Engineering [Essex] [CSEE]
Besacier, Laurent [Auteur]
Institut universitaire de France [IUF]
Traitement du Langage Parlé [TLP]
Zanon Boito, Marcely [Auteur]
Laboratoire d'Informatique de Grenoble [LIG ]
Ondel, Lucas [Auteur]
Brno University of Technology [Brno] [BUT]
Berard, Alexandre [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Yvon, François [Auteur]
Traitement du Langage Parlé [TLP]
Villavicencio, Aline [Auteur]
School of Computer Science and Electronic Engineering [Essex] [CSEE]
Besacier, Laurent [Auteur]
Institut universitaire de France [IUF]
Conference title :
Interspeech 2018
City :
Hyderabad
Country :
Inde
Start date of the conference :
2018-09
HAL domain(s) :
Informatique [cs]/Informatique et langage [cs.CL]
English abstract : [en]
We present a first attempt to perform attentional word segmen-tation directly from the speech signal, with the final goal to automatically identify lexical units in a low-resource, unwritten language (UL). Our methodology ...
Show more >We present a first attempt to perform attentional word segmen-tation directly from the speech signal, with the final goal to automatically identify lexical units in a low-resource, unwritten language (UL). Our methodology assumes a pairing between recordings in the UL with translations in a well-resourced language. It uses Acoustic Unit Discovery (AUD) to convert speech into a sequence of pseudo-phones that is segmented using neural soft-alignments produced by a neural machine translation model. Evaluation uses an actual Bantu UL, Mboshi; comparisons to monolingual and bilingual baselines illustrate the potential of attentional word segmentation for language documentation.Show less >
Show more >We present a first attempt to perform attentional word segmen-tation directly from the speech signal, with the final goal to automatically identify lexical units in a low-resource, unwritten language (UL). Our methodology assumes a pairing between recordings in the UL with translations in a well-resourced language. It uses Acoustic Unit Discovery (AUD) to convert speech into a sequence of pseudo-phones that is segmented using neural soft-alignments produced by a neural machine translation model. Evaluation uses an actual Bantu UL, Mboshi; comparisons to monolingual and bilingual baselines illustrate the potential of attentional word segmentation for language documentation.Show less >
Language :
Anglais
Peer reviewed article :
Oui
Audience :
Internationale
Popular science :
Non
ANR Project :
Collections :
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