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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 2 of 2 1 Whodunnit - searching for the most important feature types signalling emotion-related user states in speech Schuller, Björn; Kessous, Loic; Batliner, Anton... In: Computer speech and language. - Amsterdam [u.a.] : Elsevier 25 (2011) 1, 4-28 BLLDB OLC Linguistik Show details 2 Whodunnit - Searching for the Most Important Feature Types Signalling Emotion-Related User States in Speech Batliner, Anton; Steidl, Stefan; Schuller, Björn; Seppi, Dino; Vogt, Thurid; Wagner, Johannes; Devillers, Laurence; Vidrascu, Laurence; Aharonson, Vered; Kessous, Loic; Amir, Noam In: ISSN: 0885-2308 ; EISSN: 1095-8363 ; Computer Speech and Language ; https://hal.archives-ouvertes.fr/hal-00661911 ; Computer Speech and Language, Elsevier, 2010, 25 (1), pp.4. ⟨10.1016/j.csl.2009.12.003⟩ (2010) Abstract: International audience ; In this article, we describe and interpret a set of acoustic and linguistic features that characterise emotional/emotion-related user states - confined to the one database processed: four classes in a German corpus of children interacting with a pet robot. To this end, we collected a very large feature vector consisting of more than 4000 features extracted at different sites. We performed extensive feature selection (Sequential Forward Floating Search) for seven acoustic and four linguistic types of features, ending up in a small number of 'most important' features which we try to interpret by discussing the impact of different feature and extraction types. We establish different measures of impact and discuss the mutual influence of acoustics and linguistics. Keyword: automatic classification; emotion; feature selection; feature types URL: https://hal.archives-ouvertes.fr/hal-00661911 https://hal.archives-ouvertes.fr/hal-00661911/document https://hal.archives-ouvertes.fr/hal-00661911/file/PEER_stage2_10.1016%252Fj.csl.2009.12.003.pdf https://doi.org/10.1016/j.csl.2009.12.003 BASE Hide details

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