LEADER 02563nam 2200361 450 001 9910510426503321 005 20230828173633.0 035 $a(CKB)4930000000238558 035 $a(NjHacI)994930000000238558 035 $a(EXLCZ)994930000000238558 100 $a20230828d2021 uy 0 101 0 $aeng 135 $aur||||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aProceedings of the 2nd on Multimodal Sentiment Analysis Challenge $eOctober 24, 2021, Virtual Event, China /$fBjo?rn W. Schuller [and four others] 210 1$aNew York :$cAssociation for Computing Machinery,$d[2021] 210 4$dİ2021 215 $a1 online resource (83 pages) $cillustrations 225 0 $aACM Conferences 311 $a1-4503-8678-4 330 $aIt is our great pleasure to welcome you to the 2nd Multimodal Sentiment Analysis Challenge and Workshop (MuSe 2021), held in conjunction with the ACM Multimedia 2021. The MuSe challenge and associated workshop continue to push the boundaries of integrated audio-visual and textual based sentiment analysis and emotion sensing. In its 2nd edition, we posed the problem of the prediction of continuous-valued dimensional affect in YouTube reviews and stress-induced scenarios. Further tasks were the classification of 5 artificially created arousal and valence classes, and the recognition of a fused physio-arousal signal also in a stressful situation. The mission of the MuSe Challenge and Workshop is to provide a common benchmark for individual multimodal information processing and to bring together the symbolic-based Sentiment Analysis and the signal-based Affective Computing communities, to compare the merits of multimodal fusion for the three core modalities under well-defined conditions. Another motivation is the need to advance sentiment and emotion recognition systems to be able to deal with unsegmented and previously unexplored naturalistic behaviour in large amounts of in-the-wild data, as this is exactly the type of data that we face in real life. As you will see, these goals have been reached with the selection of the data and the (challenge) contributions. 606 $aHuman-computer interaction$vCongresses 615 0$aHuman-computer interaction 676 $a004.019 700 $aSchuller$b Bjo?rn W.$0878409 801 0$bNjHacI 801 1$bNjHacl 906 $aBOOK 912 $a9910510426503321 996 $aProceedings of the 2nd on Multimodal Sentiment Analysis Challenge$93516916 997 $aUNINA