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Learning prosodic sequences using the fundamental frequency variation spectrum
KTH, School of Computer Science and Communication (CSC), Speech, Music and Hearing, TMH, Speech Communication and Technology. KTH, School of Computer Science and Communication (CSC), Centres, Centre for Speech Technology, CTT.ORCID iD: 0000-0001-9327-9482
KTH, School of Computer Science and Communication (CSC), Speech, Music and Hearing, TMH, Speech Communication and Technology. KTH, School of Computer Science and Communication (CSC), Centres, Centre for Speech Technology, CTT.
2008 (English)In: Proceedings of the Speech Prosody 2008 Conference, Campinas, Brazil: Editora RG/CNPq , 2008, 151-154 p.Conference paper, Published paper (Refereed)
Abstract [en]

We investigate a recently introduced vector-valued representation of fundamental frequency variation, whose properties appear to be well-suited for statistical sequence modeling. We show what the representation looks like, and apply hidden Markov models to learn prosodic sequences characteristic of higher-level turn-taking phenomena. Our analysis shows that the models learn exactly those characteristics which have been reported for the phenomena in the literature. Further refinements to the representation lead to 12-17% relative improvement in speaker change prediction for conversational spoken dialogue systems.

Place, publisher, year, edition, pages
Campinas, Brazil: Editora RG/CNPq , 2008. 151-154 p.
National Category
Computer Science Language Technology (Computational Linguistics)
Identifiers
URN: urn:nbn:se:kth:diva-51959Scopus ID: 2-s2.0-84902655943OAI: oai:DiVA.org:kth-51959DiVA: diva2:465249
Conference
[SP-2008] Speech Prosody 2008, Fourth International Conference, Campinas, Brazil, May 6-9, 2008
Note
tmh_import_11_12_14 QC 20111221Available from: 2011-12-14 Created: 2011-12-14 Last updated: 2011-12-21Bibliographically approved

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Edlund, Jens

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CiteExportLink to record
Permanent link

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Citation style
  • apa
  • harvard1
  • 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