{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,26]],"date-time":"2025-09-26T13:16:53Z","timestamp":1758892613064,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":56,"publisher":"ACM","license":[{"start":{"date-parts":[[2017,10,23]],"date-time":"2017-10-23T00:00:00Z","timestamp":1508716800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["IIS-1523162"],"award-info":[{"award-number":["IIS-1523162"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2017,10,23]]},"DOI":"10.1145\/3123266.3123413","type":"proceedings-article","created":{"date-parts":[[2017,10,20]],"date-time":"2017-10-20T13:04:26Z","timestamp":1508504666000},"page":"1743-1751","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":20,"title":["Temporally Selective Attention Model for Social and Affective State Recognition in Multimedia Content"],"prefix":"10.1145","author":[{"given":"Hongliang","family":"Yu","sequence":"first","affiliation":[{"name":"Carnegie Mellon University, Pittsburgh, PA, USA"}]},{"given":"Liangke","family":"Gui","sequence":"additional","affiliation":[{"name":"Carnegie Mellon University, Pittsburgh, PA, USA"}]},{"given":"Michael","family":"Madaio","sequence":"additional","affiliation":[{"name":"Carnegie Mellon University, Pittsburgh, PA, USA"}]},{"given":"Amy","family":"Ogan","sequence":"additional","affiliation":[{"name":"Carnegie Mellon University, Pittsburgh, PA, USA"}]},{"given":"Justine","family":"Cassell","sequence":"additional","affiliation":[{"name":"Carnegie Mellon University, Pittsburgh, PA, USA"}]},{"given":"Louis-Philippe","family":"Morency","sequence":"additional","affiliation":[{"name":"Carnegie Mellon University, Pittsburgh, PA, USA"}]}],"member":"320","published-online":{"date-parts":[[2017,10,23]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"crossref","unstructured":"Tadas Baltruvsaitis Peter Robinson and Louis-Philippe Morency. 2016. Openface: an open source facial behavior analysis toolkit WACV.  Tadas Baltruvsaitis Peter Robinson and Louis-Philippe Morency. 2016. Openface: an open source facial behavior analysis toolkit WACV.","DOI":"10.1109\/WACV.2016.7477553"},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1145\/2964284.2967196"},{"volume-title":"Empirical evaluation of gated recurrent neural networks on sequence modeling. arXiv preprint arXiv:1412.3555","year":"2014","author":"Chung Junyoung","key":"e_1_3_2_1_3_1"},{"key":"e_1_3_2_1_4_1","unstructured":"Andrew M Dai and Quoc V Le. 2015. Semi-supervised sequence learning. In Advances in Neural Information Processing Systems. 3079--3087.   Andrew M Dai and Quoc V Le. 2015. Semi-supervised sequence learning. In Advances in Neural Information Processing Systems. 3079--3087."},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1145\/2993148.2993174"},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2014.6853739"},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"crossref","unstructured":"Zhi-Hong Deng Hongliang Yu and Yunlun Yang. 2016. Identifying Sentiment Words Using an Optimization Model with L1 Regularization AAAI.   Zhi-Hong Deng Hongliang Yu and Yunlun Yang. 2016. Identifying Sentiment Words Using an Optimization Model with L1 Regularization AAAI.","DOI":"10.1609\/aaai.v30i1.9968"},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"crossref","unstructured":"Li Dong Furu Wei Chuanqi Tan Duyu Tang Ming Zhou and Ke Xu. 2014. Adaptive Recursive Neural Network for Target-dependent Twitter Sentiment Classification. In ACL.  Li Dong Furu Wei Chuanqi Tan Duyu Tang Ming Zhou and Ke Xu. 2014. Adaptive Recursive Neural Network for Target-dependent Twitter Sentiment Classification. In ACL.","DOI":"10.3115\/v1\/P14-2009"},{"volume-title":"Austin Matthews, and Noah A Smith","year":"2015","author":"Dyer Chris","key":"e_1_3_2_1_9_1"},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2009.167"},{"volume-title":"Representation Learning for Speech Emotion Recognition. Interspeech","year":"2016","author":"Ghosh Sayan","key":"e_1_3_2_1_11_1"},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"crossref","unstructured":"Alex Graves Navdeep Jaitly and Abdel-rahman Mohamed. 2013. Hybrid speech recognition with deep bidirectional LSTM ASRU.  Alex Graves Navdeep Jaitly and Abdel-rahman Mohamed. 2013. Hybrid speech recognition with deep bidirectional LSTM ASRU.","DOI":"10.1109\/ASRU.2013.6707742"},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1997.9.8.1735"},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1145\/1014052.1014073"},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"crossref","unstructured":"Mohit Iyyer Varun Manjunatha Jordan Boyd-Graber and Hal Daum\u00e9 III. 2015. Deep Unordered Composition Rivals Syntactic Methods for Text Classification ACL.  Mohit Iyyer Varun Manjunatha Jordan Boyd-Graber and Hal Daum\u00e9 III. 2015. Deep Unordered Composition Rivals Syntactic Methods for Text Classification ACL.","DOI":"10.3115\/v1\/P15-1162"},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1007\/s12193-015-0195-2"},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1145\/2993148.2993151"},{"volume-title":"Adam: A method for stochastic optimization. ICLR","year":"2015","author":"Kingma Diederik","key":"e_1_3_2_1_18_1"},{"key":"e_1_3_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.dadm.2014.11.012"},{"key":"e_1_3_2_1_20_1","volume-title":"ICML","volume":"14","author":"Le Quoc V","year":"2014"},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1145\/641007.641038"},{"key":"e_1_3_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.5555\/2002472.2002491"},{"volume-title":"Temporal Activity Detection in Untrimmed Videos with Recurrent Neural Networks. NIPS Workshop","year":"2016","author":"Montes Alberto","key":"e_1_3_2_1_23_1"},{"key":"e_1_3_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.1145\/2070481.2070509"},{"key":"e_1_3_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.1145\/2993148.2993195"},{"key":"e_1_3_2_1_26_1","doi-asserted-by":"crossref","unstructured":"Thien Hai Nguyen and Kiyoaki Shirai. 2015. PhraseRNN: Phrase Recursive Neural Network for Aspect-based Sentiment Analysis EMNLP.  Thien Hai Nguyen and Kiyoaki Shirai. 2015. PhraseRNN: Phrase Recursive Neural Network for Aspect-based Sentiment Analysis EMNLP.","DOI":"10.18653\/v1\/D15-1298"},{"key":"e_1_3_2_1_27_1","doi-asserted-by":"publisher","DOI":"10.1145\/2993148.2993168"},{"volume-title":"Dynamic binding of identity and location information: A serial model of multiple identity tracking. Cognitive psychology","year":"2008","author":"Oksama Lauri","key":"e_1_3_2_1_28_1"},{"key":"e_1_3_2_1_29_1","doi-asserted-by":"publisher","DOI":"10.3115\/1118693.1118704"},{"volume-title":"David MJ Tax, and Louis-Philippe Morency","year":"2017","author":"Pei Wenjie","key":"e_1_3_2_1_30_1"},{"key":"e_1_3_2_1_31_1","doi-asserted-by":"publisher","DOI":"10.3115\/v1\/D14-1162"},{"key":"e_1_3_2_1_32_1","unstructured":"Ver\u00f3nica P\u00e9rez-Rosas Rada Mihalcea and Louis-Philippe Morency. 2013. Utterance-Level Multimodal Sentiment Analysis. In ACL.  Ver\u00f3nica P\u00e9rez-Rosas Rada Mihalcea and Louis-Philippe Morency. 2013. Utterance-Level Multimodal Sentiment Analysis. In ACL."},{"key":"e_1_3_2_1_33_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.inffus.2017.02.003"},{"key":"e_1_3_2_1_34_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2015.01.095"},{"volume-title":"2016 IEEE 16th International Conference on. IEEE, 439--448","year":"2016","author":"Poria Soujanya","key":"e_1_3_2_1_35_1"},{"key":"e_1_3_2_1_36_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ipm.2008.09.003"},{"volume-title":"A neural attention model for abstractive sentence summarization. EMNLP","year":"2015","author":"Rush Alexander M","key":"e_1_3_2_1_37_1"},{"key":"e_1_3_2_1_38_1","doi-asserted-by":"publisher","DOI":"10.3758\/PP.70.4.732"},{"volume-title":"What are emotions? And how can they be measured? Social science information","year":"2005","author":"Scherer Klaus R","key":"e_1_3_2_1_39_1"},{"key":"e_1_3_2_1_40_1","doi-asserted-by":"publisher","DOI":"10.1023\/B:STCO.0000035301.49549.88"},{"volume-title":"et almbox","year":"2013","author":"Socher Richard","key":"e_1_3_2_1_41_1"},{"key":"e_1_3_2_1_42_1","unstructured":"Ilya Sutskever Oriol Vinyals and Quoc V Le. 2014. Sequence to sequence learning with neural networks NIPS.   Ilya Sutskever Oriol Vinyals and Quoc V Le. 2014. Sequence to sequence learning with neural networks NIPS."},{"key":"e_1_3_2_1_43_1","doi-asserted-by":"publisher","DOI":"10.1162\/COLI_a_00049"},{"key":"e_1_3_2_1_44_1","doi-asserted-by":"crossref","unstructured":"Duyu Tang Bing Qin and Ting Liu. 2016. Aspect level sentiment classification with deep memory network EMNLP.  Duyu Tang Bing Qin and Ting Liu. 2016. Aspect level sentiment classification with deep memory network EMNLP.","DOI":"10.18653\/v1\/D16-1021"},{"key":"e_1_3_2_1_45_1","doi-asserted-by":"crossref","unstructured":"Duyu Tang Furu Wei Nan Yang Ming Zhou Ting Liu and Bing Qin. 2014. Learning Sentiment-Specific Word Embedding for Twitter Sentiment Classification ACL.  Duyu Tang Furu Wei Nan Yang Ming Zhou Ting Liu and Bing Qin. 2014. Learning Sentiment-Specific Word Embedding for Twitter Sentiment Classification ACL.","DOI":"10.3115\/v1\/P14-1146"},{"key":"e_1_3_2_1_46_1","first-page":"1221","article-title":"Comparison Between GMM-SVM Sequence Kernel And GMM: Application To Speech Emotion Recognition","volume":"11","author":"Trabelsi Imen","year":"2016","journal-title":"Journal of Engineering Science and Technology"},{"key":"e_1_3_2_1_47_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2016.7472669"},{"volume-title":"Select-Additive Learning: Improving Cross-individual Generalization in Multimodal Sentiment Analysis. arXiv preprint arXiv:1609.05244","year":"2016","author":"Wang Haohan","key":"e_1_3_2_1_48_1"},{"key":"e_1_3_2_1_49_1","doi-asserted-by":"publisher","DOI":"10.1109\/MIS.2013.34"},{"key":"e_1_3_2_1_50_1","doi-asserted-by":"crossref","unstructured":"Zichao Yang Xiaodong He Jianfeng Gao Li Deng and Alex Smola. 2016. Stacked attention networks for image question answering CVPR.  Zichao Yang Xiaodong He Jianfeng Gao Li Deng and Alex Smola. 2016. Stacked attention networks for image question answering CVPR.","DOI":"10.1109\/CVPR.2016.10"},{"volume-title":"2016 a. MOSI: Multimodal Corpus of Sentiment Intensity and Subjectivity Analysis in Online Opinion Videos. arXiv preprint arXiv:1606.06259","year":"2016","author":"Zadeh Amir","key":"e_1_3_2_1_51_1"},{"key":"e_1_3_2_1_52_1","doi-asserted-by":"publisher","DOI":"10.1109\/MIS.2016.94"},{"key":"e_1_3_2_1_53_1","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2008.52"},{"volume-title":"Towards a dyadic computational model of rapport management for human-virtual agent interaction International Conference on Intelligent Virtual Agents","author":"Zhao Ran","key":"e_1_3_2_1_54_1"},{"key":"e_1_3_2_1_55_1","doi-asserted-by":"crossref","unstructured":"Ran Zhao Tanmay Sinha Alan W Black and Justine Cassell. 2016 a. Socially-aware virtual agents: Automatically assessing dyadic rapport from temporal patterns of behavior. In IVA.  Ran Zhao Tanmay Sinha Alan W Black and Justine Cassell. 2016 a. Socially-aware virtual agents: Automatically assessing dyadic rapport from temporal patterns of behavior. In IVA.","DOI":"10.1007\/978-3-319-47665-0_20"},{"key":"e_1_3_2_1_56_1","doi-asserted-by":"publisher","DOI":"10.1145\/2964284.2964289"}],"event":{"name":"MM '17: ACM Multimedia Conference","sponsor":["SIGMM ACM Special Interest Group on Multimedia"],"location":"Mountain View California USA","acronym":"MM '17"},"container-title":["Proceedings of the 25th ACM international conference on Multimedia"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3123266.3123413","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3123266.3123413","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3123266.3123413","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T02:14:03Z","timestamp":1750212843000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3123266.3123413"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,10,23]]},"references-count":56,"alternative-id":["10.1145\/3123266.3123413","10.1145\/3123266"],"URL":"https:\/\/doi.org\/10.1145\/3123266.3123413","relation":{},"subject":[],"published":{"date-parts":[[2017,10,23]]},"assertion":[{"value":"2017-10-23","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}