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010   $a3-030-22895-9
024 7 $a10.1007/978-3-030-22895-8
035   $a(CKB)4100000008747493
035   $a(MiAaPQ)EBC5838906
035   $a(DE-He213)978-3-030-22895-8
035   $z(PPN)258859210
035   $a(PPN)243770030
035   $a(EXLCZ)994100000008747493
100   $a20190724d2020      u|         0
101 0 $aeng
135   $aurcnu||||||||
181   $ctxt$2rdacontent
182   $cc$2rdamedia
183   $acr$2rdacarrier
200 14$aThe Temporal Structure of Multimodal Communication $eTheory, Methods and Applications /$fedited by Laszlo Hunyadi, István Szekrényes
205   $a1st ed. 2020.
210  1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2020.
215   $a1 online resource (168 pages)
225 1 $aIntelligent Systems Reference Library,$x1868-4394 ;$v164
311   $a3-030-22894-0 
327   $aLinguistic and Contextual Clues of Intentions and Perspectives in Human Communication -- The Teacher?s Body Communicates. Detection of Paraverbal Behaviour Patterns -- Is it Possible to Perform ?Liquefying? Actions in Conversational Analysis? The Detection of Structures in Indirect Observations -- Research Methods for Studying Daily Life: Experience Sampling and a Multilevel Approach to Study Time and Mood at Work.
330   $aThe general focus of this book is on multimodal communication, which captures the temporal patterns of behavior in various dialogue settings. After an overview of current theoretical models of verbal and nonverbal communication cues, it presents studies on a range of related topics: paraverbal behavior patterns in the classroom setting; a proposed optimal methodology for conversational analysis; a study of time and mood at work; an experiment on the dynamics of multimodal interaction from the observer?s perspective; formal cues of uncertainty in conversation; how machines can know we understand them; and detecting topic changes using neural network techniques. A joint work bringing together psychologists, communication scientists, information scientists and linguists, the book will be of interest to those working on a wide range of applications from industry to home, and from health to security, with the main goals of revealing, embedding and implementing a rich spectrum of information on human behavior. .
410  0$aIntelligent Systems Reference Library,$x1868-4394 ;$v164
606   $aComputational intelligence
606   $aArtificial intelligence
606   $aComputational linguistics
606   $aCognitive psychology
606   $aComputational Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/T11014
606   $aArtificial Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/I21000
606   $aComputational Linguistics$3https://scigraph.springernature.com/ontologies/product-market-codes/N22000
606   $aCognitive Psychology$3https://scigraph.springernature.com/ontologies/product-market-codes/Y20060
615  0$aComputational intelligence.
615  0$aArtificial intelligence.
615  0$aComputational linguistics.
615  0$aCognitive psychology.
615 14$aComputational Intelligence.
615 24$aArtificial Intelligence.
615 24$aComputational Linguistics.
615 24$aCognitive Psychology.
676   $a410.285
676   $a006.35
702   $aHunyadi$b Laszlo$4edt$4http://id.loc.gov/vocabulary/relators/edt
702   $aSzekrényes$b István$4edt$4http://id.loc.gov/vocabulary/relators/edt
906   $aBOOK
912   $a9910483428203321
996   $aThe Temporal Structure of Multimodal Communication$92226080
997   $aUNINA