kth.sePublikationer KTH
Ändra sökning
RefereraExporteraLänk till posten
Permanent länk

Direktlänk
Referera
Referensformat
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Annat format
Fler format
Språk
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Annat språk
Fler språk
Utmatningsformat
  • html
  • text
  • asciidoc
  • rtf
Projection of Turn Completion in Incremental Spoken Dialogue Systems
KTH, Skolan för elektroteknik och datavetenskap (EECS), Intelligenta system, Tal, musik och hörsel, TMH.ORCID-id: 0000-0003-3513-4132
KTH, Skolan för elektroteknik och datavetenskap (EECS), Intelligenta system, Tal, musik och hörsel, TMH.ORCID-id: 0000-0002-8579-1790
2021 (Engelska)Ingår i: SIGDIAL 2021: SIGDIAL 2021 - 22nd Annual Meeting of the Special Interest Group on Discourse and Dialogue, Proceedings of the Conference, Virtual, Singapore 29 July 2021 through 31 July 2021, ASSOC COMPUTATIONAL LINGUISTICS , 2021, s. 431-437Konferensbidrag, Publicerat paper (Refereegranskat)
Abstract [en]

The ability to take turns in a fluent way (i.e., without long response delays or frequent interruptions) is a fundamental aspect of any spoken dialog system. However, practical speech recognition services typically induce a long response delay, as it takes time before the processing of the user's utterance is complete. There is a considerable amount of research indicating that humans achieve fast response times by projecting what the interlocutor will say and estimating upcoming turn completions. In this work, we implement this mechanism in an incremental spoken dialog system, by using a language model that generates possible futures to project upcoming completion points. In theory, this could make the system more responsive, while still having access to semantic information not yet processed by the speech recognizer. We conduct a small study which indicates that this is a viable approach for practical dialog systems, and that this is a promising direction for future research.

Ort, förlag, år, upplaga, sidor
ASSOC COMPUTATIONAL LINGUISTICS , 2021. s. 431-437
Nationell ämneskategori
Datavetenskap (datalogi)
Identifikatorer
URN: urn:nbn:se:kth:diva-304761DOI: 10.18653/v1/2021.sigdial-1.45ISI: 000707001800045Scopus ID: 2-s2.0-85136067428OAI: oai:DiVA.org:kth-304761DiVA, id: diva2:1610961
Konferens
22nd Annual Meeting of the Special-Interest-Group-on-Discourse-and-Dialogue (SIGDIAL), JUL 29-31, 2021, Singapore, SINGAPORE
Projekt
tmh_turntaking
Anmärkning

Part of proceedings: ISBN 978-1-954085-81-7, QC 20230117

Tillgänglig från: 2021-11-12 Skapad: 2021-11-12 Senast uppdaterad: 2025-05-27Bibliografiskt granskad

Open Access i DiVA

Fulltext saknas i DiVA

Övriga länkar

Förlagets fulltextScopus

Person

Ekstedt, ErikSkantze, Gabriel

Sök vidare i DiVA

Av författaren/redaktören
Ekstedt, ErikSkantze, Gabriel
Av organisationen
Tal, musik och hörsel, TMH
Datavetenskap (datalogi)

Sök vidare utanför DiVA

GoogleGoogle Scholar

doi
urn-nbn

Altmetricpoäng

doi
urn-nbn
Totalt: 184 träffar
RefereraExporteraLänk till posten
Permanent länk

Direktlänk
Referera
Referensformat
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Annat format
Fler format
Språk
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Annat språk
Fler språk
Utmatningsformat
  • html
  • text
  • asciidoc
  • rtf