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Using generalized additive models and random forests to model prosodic prominence in German

  • The perception of prosodic prominence is influenced by different sources like different acoustic cues, linguistic expectations and context. We use a generalized additive model and a random forest to model the perceived prominence on a corpus of spoken German. Both models are able to explain over 80% of the variance. While the random forests give us some insights on the relative importance of the cues, the general additive model gives us insights on the interaction between different cues to prominence.

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Metadaten
Author:Denis Arnold, Petra Wagner, R. Harald BaayenGND
URN:urn:nbn:de:bsz:mh39-59553
URL:http://www.isca-speech.org/archive/archive_papers/interspeech_2013/i13_0272.pdf
ISBN:978-1-62993-443-3
ISSN:2308-457X
Parent Title (English):14th Annual Conference of the International Speech Communication Association (INTERSPEECH 2013), Lyon, France, 25-29 August 2013
Publisher:International Speech Communications Association
Editor:F. Bimbot, C. Cerisara, C. Fougeron, G. Gravier, L. Lamel, F. Pellegrino, P. Perrier
Document Type:Conference Proceeding
Language:English
Year of first Publication:2013
Date of Publication (online):2017/03/07
Reviewstate:Peer-Review
Tag:gam; prominence; prosody; random forests
GND Keyword:Prosodie
First Page:272
Last Page:276
Dewey Decimal Classification:400 Sprache / 400 Sprache, Linguistik
Leibniz-Classification:Sprache, Linguistik
Linguistics-Classification:Phonetik / Phonologie
Open Access?:Ja
Licence (German):Es gilt das UrhG