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Comparative Analysis of Prosodic Characteristics Using WaveNet Embeddings
Stockholm University, Faculty of Humanities, Department of Linguistics, Phonetics.ORCID iD: 0000-0003-3824-2980
2019 (English)In: Proceedings of Interspeech 2019 / [ed] Gernot Kubin, Zdravko Kačič, The International Speech Communication Association (ISCA), 2019, p. 2538-2542Conference paper, Published paper (Refereed)
Abstract [en]

We present a methodology for assessing similarities and differences between language varieties and dialects in terms of prosodic characteristics. A multi-speaker, multi-dialect WaveNet network is trained on low sample-rate signal retaining only prosodic characteristics of the original speech. The network is conditioned on labels related to speakers’ region or dialect. The resulting conditioning embeddings are subsequently used as a multi-dimensional characteristics of different language varieties, with results consistent with dialectological studies. The method and results are illustrated on a Swedia 2000 corpus of Swedish dialectal variation.

Place, publisher, year, edition, pages
The International Speech Communication Association (ISCA), 2019. p. 2538-2542
Series
Interspeech, E-ISSN 1990-9772
National Category
General Language Studies and Linguistics
Research subject
Phonetics
Identifiers
URN: urn:nbn:se:su:diva-173515DOI: 10.21437/Interspeech.2019-2373OAI: oai:DiVA.org:su-173515DiVA, id: diva2:1354347
Conference
Interspeech 2019, Graz, Austria, 15-19 September 2019
Available from: 2019-09-25 Created: 2019-09-25 Last updated: 2019-09-25Bibliographically approved

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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