Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Multimodal language acquisition based on motor learning and interaction
Institute for System and Robotics (ISR), Instituto Superior Técnico, Lisbon, Portugal. (VISLAB)
Stockholm University, Faculty of Humanities, Department of Linguistics, Phonetics.ORCID iD: 0000-0003-3981-2551
Institute for System and Robotics (ISR), Instituto Superior Técnico, Lisbon, Portugal. (VISLAB)
Stockholm University, Faculty of Humanities, Department of Linguistics, Phonetics. (Language development)ORCID iD: 0000-0002-7980-3601
2010 (English)In: From Motor Learning to Interaction Learning in Robots / [ed] Olivier Sigaud & jan Peters, Springer Berlin/Heidelberg, 2010, 467-489 p.Chapter in book (Other academic)
Abstract [en]

In this work we propose a methodology for language acquisition in humanoid robots that mimics that in children. Language acquisition is a complex process that involves mastering several different tasks, such as producing speech sounds, learning how to group different sounds into a consistent and manageable number of classes or speech units, grounding speech, and recognizing the speech sounds when uttered by other persons. While it is not known to which extent those abilities are learned or written in our genetic code, this work aims at two intertwined goals: (i) to investigate how much of linguistic structure that can be derived directly from the speech signal directed to infants by (ii) designing, building and testing biological plausible models for language acquisition in a humanoid robot. We have therefore chosen to avoid implementing any pre-programmed linguistic knowledge, such as phonemes, into these models. Instead we rely on general methods such as pattern matching and hierarchical clustering techniques, and show that it is possible to acquire important linguistic structures directly from the speech signal through the interaction with a caregiver. We also show that this process can be facilitated through the use of motor learning.

Place, publisher, year, edition, pages
Springer Berlin/Heidelberg, 2010. 467-489 p.
Series
Studies in Computational Intelligence, ISSN 1860-949X ; 264
National Category
Robotics General Language Studies and Linguistics
Identifiers
URN: urn:nbn:se:su:diva-32985DOI: 10.1007/978-3-642-05181-4_20ISBN: 978-3-642-05180-7 (print)OAI: oai:DiVA.org:su-32985DiVA: diva2:282107
Available from: 2010-01-15 Created: 2009-12-18 Last updated: 2014-04-29Bibliographically approved

Open Access in DiVA

fulltext(382 kB)412 downloads
File information
File name FULLTEXT01.pdfFile size 382 kBChecksum SHA-512
e2aa65bdc3d887b8c3298280323a0480e180b6be82e695b451335783834311bdb7255d4fe7753ad133bb82fc8c1de881fc94365d2cd9a0b3ad41e68b3b2d8cda
Type fulltextMimetype application/pdf

Other links

Publisher's full text

Search in DiVA

By author/editor
Gustavsson, LisaLacerda, Francisco
By organisation
Phonetics
RoboticsGeneral Language Studies and Linguistics

Search outside of DiVA

GoogleGoogle Scholar
Total: 412 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

doi
isbn
urn-nbn

Altmetric score

doi
isbn
urn-nbn
Total: 130 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf