{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,26]],"date-time":"2026-02-26T15:30:24Z","timestamp":1772119824594,"version":"3.50.1"},"reference-count":78,"publisher":"Springer Science and Business Media LLC","issue":"4","license":[{"start":{"date-parts":[[2024,3,22]],"date-time":"2024-03-22T00:00:00Z","timestamp":1711065600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,3,22]],"date-time":"2024-03-22T00:00:00Z","timestamp":1711065600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"name":"UBC Office of the Vice-President, Research and Innovation"},{"DOI":"10.13039\/501100004489","name":"Mitacs","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100004489","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["User Model User-Adap Inter"],"published-print":{"date-parts":[[2024,9]]},"DOI":"10.1007\/s11257-024-09394-1","type":"journal-article","created":{"date-parts":[[2024,3,22]],"date-time":"2024-03-22T04:17:08Z","timestamp":1711081028000},"page":"1327-1367","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Personalization of industrial human\u2013robot communication through domain adaptation based on user feedback"],"prefix":"10.1007","volume":"34","author":[{"given":"Debasmita","family":"Mukherjee","sequence":"first","affiliation":[]},{"given":"Jayden","family":"Hong","sequence":"additional","affiliation":[]},{"given":"Haripriya","family":"Vats","sequence":"additional","affiliation":[]},{"given":"Sooyeon","family":"Bae","sequence":"additional","affiliation":[]},{"given":"Homayoun","family":"Najjaran","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,3,22]]},"reference":[{"key":"9394_CR1","unstructured":"Affectiva. Building the ultimate in-cabin experience with renovo and affectiva (2018)"},{"issue":"1","key":"9394_CR2","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1177\/1529100619832930","volume":"20","author":"LF Barrett","year":"2019","unstructured":"Barrett, L.F., Adolphs, R., Marsella, S., Martinez, A.M., Pollak, S.D.: Emotional expressions reconsidered: challenges to inferring emotion from human facial movements. Psychol. Sci. Public Interest 20(1), 1\u201368 (2019). (PMID: 31313636)","journal-title":"Psychol. Sci. Public Interest"},{"issue":"3","key":"9394_CR3","doi-asserted-by":"publisher","first-page":"153","DOI":"10.1080\/01972243.2018.1444255","volume":"34","author":"P Caleb-Solly","year":"2018","unstructured":"Caleb-Solly, P., Dogramadzi, S., Huijnen, C.A., van den Heuvel, H.: Exploiting ability for human adaptation to facilitate improved human-robot interaction and acceptance. Inf. Soc. 34(3), 153\u2013165 (2018)","journal-title":"Inf. Soc."},{"issue":"9","key":"9394_CR4","doi-asserted-by":"publisher","first-page":"12751","DOI":"10.1007\/s11042-022-14050-0","volume":"82","author":"G Castellano","year":"2022","unstructured":"Castellano, G., Carolis, B.D., Macchiarulo, N.: Automatic facial emotion recognition at the COVID-19 pandemic time. Multimedia Tools Appl. 82(9), 12751\u201312769 (2022)","journal-title":"Multimedia Tools Appl."},{"key":"9394_CR5","doi-asserted-by":"crossref","unstructured":"Chatfield, K., Simonyan, K., Vedaldi, A., Zisserman, A.: Return of the devil in the details: delving deep into convolutional nets (2014)","DOI":"10.5244\/C.28.6"},{"key":"9394_CR6","doi-asserted-by":"publisher","first-page":"49","DOI":"10.1016\/j.ins.2017.10.044","volume":"428","author":"L Chen","year":"2018","unstructured":"Chen, L., Zhou, M., Su, W., Wu, M., She, J., Hirota, K.: Softmax regression based deep sparse autoencoder network for facial emotion recognition in human\u2013robot interaction. Inf. Sci. 428, 49\u201361 (2018)","journal-title":"Inf. Sci."},{"key":"9394_CR7","doi-asserted-by":"publisher","DOI":"10.1016\/j.artmed.2022.102256","volume":"125","author":"S Chi","year":"2022","unstructured":"Chi, S., Tian, Y., Wang, F., Zhou, T., Jin, S., Li, J.: A novel lifelong machine learning-based method to eliminate calibration drift in clinical prediction models. Artif. Intell. Med. 125, 102256 (2022)","journal-title":"Artif. Intell. Med."},{"key":"9394_CR8","doi-asserted-by":"crossref","unstructured":"Chiurco, A., Frangella, J., Longo, F., Nicoletti, L., Padovano, A., Solina, V., Mirabelli, G., Citraro, C.: Real-time detection of worker\u2019s emotions for advanced human-robot interaction during collaborative tasks in smart factories. In: Procedia Computer Science, 3rd International Conference on Industry 4.0 and Smart Manufacturing, vol. 200, pp. 1875\u20131884 (2022)","DOI":"10.1016\/j.procs.2022.01.388"},{"key":"9394_CR9","doi-asserted-by":"crossref","unstructured":"Churamani, N., Anton, P., Br\u00fcgger, M., Flie\u00dfwasser, E., Hummel, T., Mayer, J., Mustafa, W., Ng, H.\u00a0G., Nguyen, T. L.\u00a0C., Nguyen, Q., Soll, M., Springenberg, S., Griffiths, S., Heinrich, S., Navarro-Guerrero, N., Strahl, E., Twiefel, J., Weber, C., and Wermter, S.: The impact of personalisation on human-robot interaction in learning scenarios. In: Proceedings of the 5th International Conference on Human Agent Interaction, HAI \u201917, 171\u2013180, New York, NY, USA. Association for Computing Machinery (2017)","DOI":"10.1145\/3125739.3125756"},{"key":"9394_CR10","doi-asserted-by":"publisher","first-page":"79","DOI":"10.1016\/j.neuropsychologia.2014.01.002","volume":"56","author":"FM Citron","year":"2014","unstructured":"Citron, F.M., Gray, M.A., Critchley, H.D., Weekes, B.S., Ferstl, E.C.: Emotional valence and arousal affect reading in an interactive way: neuroimaging evidence for an approach-withdrawal framework. Neuropsychologia 56, 79\u201389 (2014)","journal-title":"Neuropsychologia"},{"key":"9394_CR11","doi-asserted-by":"crossref","unstructured":"Di\u00a0Napoli, C., Valentino, M., Sabatucci, L., Cossentino, M.: Adaptive workflows of home-care services. In: 2018 IEEE 27th International Conference on Enabling Technologies: Infrastructure for Collaborative Enterprises (WETICE), 3\u20138 (2018)","DOI":"10.1109\/WETICE.2018.00008"},{"key":"9394_CR12","doi-asserted-by":"crossref","unstructured":"Drawdy, C.\u00a0C., Yanik, P.\u00a0M.: Gaze estimation technique for directing assistive robotics. In: Procedia Manufacturing, 6th International Conference on Applied Human Factors and Ergonomics (AHFE 2015) and the Affiliated Conferences, AHFE 2015, vol. 3, pp. 837\u2013844 (2015)","DOI":"10.1016\/j.promfg.2015.07.339"},{"key":"9394_CR13","unstructured":"Ekman, P.: Emotions revealed: Recognizing faces and feelings to improve communication and emotional life. Emotions revealed: Recognizing faces and feelings to improve communication and emotional life. Times Books\/Henry Holt and Co, New York, NY, US. Pages: xvii, 267 (2003)"},{"key":"9394_CR14","volume-title":"Unmasking the face","author":"P Ekman","year":"2003","unstructured":"Ekman, P., Friesen, W.V.: Unmasking the face. Malor Books, Cambridge, MA (2003)"},{"key":"9394_CR15","doi-asserted-by":"crossref","unstructured":"Faria, D.\u00a0R., Vieira, M., Faria, F.\u00a0C., Premebida, C.: Affective facial expressions recognition for human-robot interaction. In: 2017 26th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN), pp. 805\u2013810. IEEE (2017)","DOI":"10.1109\/ROMAN.2017.8172395"},{"key":"9394_CR16","doi-asserted-by":"crossref","unstructured":"Gajhede, N., Beck, O., Purwins, H.: Convolutional neural networks with batch normalization for classifying hi-hat, snare, and bass percussion sound samples. In: Proceedings of the Audio Mostly 2016, AM \u201916, pp. 111\u2013115, New York, NY, USA. Association for Computing Machinery (2016)","DOI":"10.1145\/2986416.2986453"},{"key":"9394_CR17","unstructured":"Gal, Y., Ghahramani, Z.: Dropout as a bayesian approximation: Representing model uncertainty in deep learning. In: International Conference on Machine Learning, 1050\u20131059. PMLR (2016)"},{"key":"9394_CR18","doi-asserted-by":"crossref","unstructured":"Girshick, R., Donahue, J., Darrell, T., Malik, J.: Rich feature hierarchies for accurate object detection and semantic segmentation (2013)","DOI":"10.1109\/CVPR.2014.81"},{"key":"9394_CR19","doi-asserted-by":"crossref","unstructured":"Goodfellow, I.\u00a0J., Erhan, D., Carrier, P.\u00a0L., Courville, A., Mirza, M., Hamner, B., Cukierski, W., Tang, Y., Thaler, D., Lee, D.-H., Zhou, Y., Ramaiah, C., Feng, F., Li, R., Wang, X., Athanasakis, D., Shawe-Taylor, J., Milakov, M., Park, J., Ionescu, R., Popescu, M., Grozea, C., Bergstra, J., Xie, J., Romaszko, L., Xu, B., Chuang, Z., Bengio, Y.: Challenges in representation learning: a report on three machine learning contests (2013)","DOI":"10.1007\/978-3-642-42051-1_16"},{"key":"9394_CR20","doi-asserted-by":"crossref","unstructured":"Gupta, S., Hoffman, J., Malik, J.: Cross modal distillation for supervision transfer (2015)","DOI":"10.1109\/CVPR.2016.309"},{"key":"9394_CR21","unstructured":"Hendrycks, D., Gimpel, K.: A baseline for detecting misclassified and out-of-distribution examples in neural networks (2016)"},{"key":"9394_CR22","unstructured":"Hinton, G., Vinyals, O., Dean, J.: Distilling the knowledge in a neural network (2015)"},{"key":"9394_CR23","doi-asserted-by":"crossref","unstructured":"Hsu, S.-C., Huang, H.-H., Huang, C.-L.: Facial expression recognition for human-robot interaction. In: 2017 First IEEE International Conference on Robotic Computing (IRC), pp. 1\u20137 (2017)","DOI":"10.1109\/IRC.2017.12"},{"key":"9394_CR24","doi-asserted-by":"publisher","first-page":"274","DOI":"10.1007\/978-3-030-96040-7_22","volume-title":"Advanced Network Technologies and Intelligent Computing","author":"YV Kale","year":"2022","unstructured":"Kale, Y.V., Shetty, A.U., Patil, Y.A., Patil, R.A., Medhane, D.V.: Object detection and face recognition using yolo and inception model. In: Woungang, I., Dhurandher, S.K., Pattanaik, K.K., Verma, A., Verma, P. (eds.) Advanced Network Technologies and Intelligent Computing, pp. 274\u2013287. Springer International Publishing, Cham (2022)"},{"key":"9394_CR25","doi-asserted-by":"publisher","first-page":"15","DOI":"10.1016\/j.procir.2018.03.027","volume":"72","author":"C Kardos","year":"2018","unstructured":"Kardos, C., Kem\u00e9ny, Z., Kov\u00e1cs, A., Pataki, B.E., V\u00e1ncza, J.: Context-dependent multimodal communication in human-robot collaboration. Procedia CIRP 72, 15\u201320 (2018)","journal-title":"Procedia CIRP"},{"key":"9394_CR26","doi-asserted-by":"publisher","first-page":"512","DOI":"10.1016\/j.wneu.2020.04.022","volume":"140","author":"O Khan","year":"2020","unstructured":"Khan, O., Badhiwala, J.H., Grasso, G., Fehlings, M.G.: Use of machine learning and artificial intelligence to drive personalized medicine approaches for spine care. World Neurosurg. 140, 512\u2013518 (2020)","journal-title":"World Neurosurg."},{"key":"9394_CR27","doi-asserted-by":"crossref","unstructured":"Kim, D.\u00a0Y., Wallraven, C.: Label quality in affectnet: results of crowd-based re-annotation (2021)","DOI":"10.1007\/978-3-031-02444-3_39"},{"key":"9394_CR28","doi-asserted-by":"publisher","first-page":"126","DOI":"10.1016\/j.engappai.2016.02.018","volume":"52","author":"J-B Kim","year":"2016","unstructured":"Kim, J.-B., Park, J.-S.: Multistage data selection-based unsupervised speaker adaptation for personalized speech emotion recognition. Eng. Appl. Artif. Intell. 52, 126\u2013134 (2016)","journal-title":"Eng. Appl. Artif. Intell."},{"issue":"11","key":"9394_CR29","first-page":"2755","volume":"42","author":"R Kosti","year":"2019","unstructured":"Kosti, R., Alvarez, J.M., Recasens, A., Lapedriza, A.: Context based emotion recognition using emotic dataset. IEEE Trans. Pattern Anal. Mach. Intell. 42(11), 2755\u20132766 (2019)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"9394_CR30","doi-asserted-by":"crossref","unstructured":"Kothandaraman, D., Nambiar, A., Mittal, A.: Domain adaptive knowledge distillation for driving scene semantic segmentation (2020)","DOI":"10.1109\/WACVW52041.2021.00019"},{"key":"9394_CR31","unstructured":"Krizhevsky, A., Sutskever, I., Hinton, G.E.: Imagenet classification with deep convolutional neural networks. In: Proceedings of the 25th International Conference on Neural Information Processing Systems - Volume 1, NIPS\u201912, pp. 1097\u20131105, Red Hook, NY, USA. Curran Associates Inc (2012)"},{"key":"9394_CR32","doi-asserted-by":"crossref","unstructured":"Kumagai, K., Lin, D., Meng, L., Blidaru, A., Beesley, P., Kuli\u0107, D., Mizuuchi, I.: Towards individualized affective human-machine interaction. In: 2018 27th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN), pp. 678\u2013685 (2018)","DOI":"10.1109\/ROMAN.2018.8525679"},{"key":"9394_CR33","doi-asserted-by":"crossref","unstructured":"Lin, T.-Y., Maire, M., Belongie, S., Bourdev, L., Girshick, R., Hays, J., Perona, P., Ramanan, D., Zitnick, C.\u00a0L., Doll\u00e1r, P.: Microsoft coco: Common objects in context (2014)","DOI":"10.1007\/978-3-319-10602-1_48"},{"key":"9394_CR34","doi-asserted-by":"publisher","first-page":"74762","DOI":"10.1109\/ACCESS.2018.2884793","volume":"6","author":"H Liu","year":"2018","unstructured":"Liu, H., Fang, T., Zhou, T., Wang, L.: Towards robust human-robot collaborative manufacturing: Multimodal fusion. IEEE Access 6, 74762\u201374771 (2018)","journal-title":"IEEE Access"},{"issue":"4","key":"9394_CR35","doi-asserted-by":"publisher","first-page":"668","DOI":"10.1109\/JAS.2017.7510622","volume":"4","author":"Z Liu","year":"2017","unstructured":"Liu, Z., Wu, M., Cao, W., Chen, L., Xu, J., Zhang, R., Zhou, M., Mao, J.: A facial expression emotion recognition based human\u2013robot interaction system. IEEE\/CAA J. Automatica Sinica 4(4), 668\u2013676 (2017)","journal-title":"IEEE\/CAA J. Automatica Sinica"},{"key":"9394_CR36","doi-asserted-by":"crossref","unstructured":"Long, J., Shelhamer, E., Darrell, T.: Fully convolutional networks for semantic segmentation (2014)","DOI":"10.1109\/CVPR.2015.7298965"},{"key":"9394_CR37","doi-asserted-by":"crossref","unstructured":"Lucey, P., Cohn, J.\u00a0F., Kanade, T., Saragih, J., Ambadar, Z., Matthews, I.: The extended cohn-kanade dataset (ck+): A complete dataset for action unit and emotion-specified expression. In: 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Workshops, 94\u2013101 (2010)","DOI":"10.1109\/CVPRW.2010.5543262"},{"key":"9394_CR38","doi-asserted-by":"publisher","DOI":"10.1016\/j.engappai.2022.105631","volume":"117","author":"M Maroto-G\u00f3mez","year":"2023","unstructured":"Maroto-G\u00f3mez, M., Marqu\u00e9s-Villaroya, S., Castillo, J.C., Castro-Gonz\u00e1lez, \u00c1., Malfaz, M.: Active learning based on computer vision and human-robot interaction for the user profiling and behavior personalization of an autonomous social robot. Eng. Appl. Artif. Intell. 117, 105631 (2023)","journal-title":"Eng. Appl. Artif. Intell."},{"key":"9394_CR39","doi-asserted-by":"crossref","unstructured":"Maurtua, I., Fernandez, I., Kildal, J., Susperregi, L., Tellaeche, A., Ibarguren, A.: Enhancing safe human-robot collaboration through natural multimodal communication. In: 2016 IEEE 21st International Conference on Emerging Technologies and Factory Automation (ETFA), 1\u20138 (2016)","DOI":"10.1109\/ETFA.2016.7733573"},{"issue":"4","key":"9394_CR40","doi-asserted-by":"crossref","first-page":"172988141771604","DOI":"10.1177\/1729881417716043","volume":"14","author":"I Maurtua","year":"2017","unstructured":"Maurtua, I., Fern\u00e1ndez, I., Tellaeche, A., Kildal, J., Susperregi, L., Ibarguren, A., Sierra, B.: Natural multimodal communication for human-robot collaboration. Int. J. Adv. Rob. Syst. 14(4), 1729881417716043 (2017)","journal-title":"Int. J. Adv. Rob. Syst."},{"key":"9394_CR41","doi-asserted-by":"publisher","first-page":"21","DOI":"10.3390\/sym12010021","volume":"12","author":"O Mitru\u0163","year":"2019","unstructured":"Mitru\u0163, O., Moise, G., Petrescu, L., Moldoveanu, A., Leordeanu, M., Moldoveanu, F.: Emotion classification based on biophysical signals and machine learning techniques. Symmetry 12, 21 (2019)","journal-title":"Symmetry"},{"issue":"2","key":"9394_CR42","first-page":"125","volume":"28","author":"SN Mohammed","year":"2020","unstructured":"Mohammed, S.N., Hassan, A.K.A.: A survey on emotion recognition for human robot interaction. J. Comput. Inf. Technol. 28(2), 125\u2013146 (2020)","journal-title":"J. Comput. Inf. Technol."},{"issue":"1","key":"9394_CR43","doi-asserted-by":"publisher","first-page":"18","DOI":"10.1109\/TAFFC.2017.2740923","volume":"10","author":"A Mollahosseini","year":"2019","unstructured":"Mollahosseini, A., Hasani, B., Mahoor, M.H.: AffectNet: A database for facial expression, valence, and arousal computing in the wild. IEEE Trans. Affect. Comput. 10(1), 18\u201331 (2019)","journal-title":"IEEE Trans. Affect. Comput."},{"key":"9394_CR44","unstructured":"Mozilla (2022). Mozilla common voice, https:\/\/voice.mozilla.org\/en"},{"key":"9394_CR45","unstructured":"Mukherjee, D.: Statistically-informed multimodal domain adaptation in industrial human-robot collaboration environments. PhD thesis, University of British Columbia (2023)"},{"key":"9394_CR46","doi-asserted-by":"publisher","DOI":"10.1016\/j.rcim.2021.102231","volume":"73","author":"D Mukherjee","year":"2022","unstructured":"Mukherjee, D., Gupta, K., Chang, L.H., Najjaran, H.: A survey of robot learning strategies for human-robot collaboration in industrial settings. Robot. Comput. Integr. Manuf. 73, 102231 (2022)","journal-title":"Robot. Comput. Integr. Manuf."},{"key":"9394_CR47","doi-asserted-by":"crossref","unstructured":"Mukherjee, D., Gupta, K., Najjaran, H.: An ai-powered hierarchical communication framework for robust human-robot collaboration in industrial settings. In: 2022 31st IEEE International Conference on Robot & Human Interactive Communication (RO-MAN),accepted, in press, pp. 1\u20136 (2022b)","DOI":"10.1109\/RO-MAN53752.2022.9900601"},{"key":"9394_CR48","first-page":"9","volume":"I","author":"D Mukherjee","year":"2022","unstructured":"Mukherjee, D., Gupta, K., Najjaran, H.: A critical analysis of industrial human-robot communication and its quest for naturalness through the lens of complexity theory. Front. Robot. A I, 9 (2022)","journal-title":"Front. Robot. A"},{"key":"9394_CR49","unstructured":"Mukherjee, D., Singhai, R., Najjaran, H.: Systematic adaptation of communication-focused machine learning models from real to virtual environments for human-robot collaboration (2023)"},{"key":"9394_CR50","doi-asserted-by":"publisher","DOI":"10.2196\/34989","volume":"7","author":"R Nandy","year":"2023","unstructured":"Nandy, R., Nandy, K., Walters, S.T.: Relationship between valence and arousal for subjective experience in a real-life setting for supportive housing residents: Results from an ecological momentary assessment study. JMIR Format. Res. 7, e34989 (2023)","journal-title":"JMIR Format. Res."},{"key":"9394_CR51","doi-asserted-by":"publisher","DOI":"10.1016\/j.rcim.2020.102085","volume":"68","author":"C Nuzzi","year":"2021","unstructured":"Nuzzi, C., Pasinetti, S., Pagani, R., Ghidini, S., Beschi, M., Coffetti, G., Sansoni, G.: Meguru: a gesture-based robot program builder for meta-collaborative workstations. Robot. Comput. Integr. Manuf. 68, 102085 (2021)","journal-title":"Robot. Comput. Integr. Manuf."},{"issue":"10","key":"9394_CR52","doi-asserted-by":"publisher","first-page":"957","DOI":"10.3390\/machines10100957","volume":"10","author":"S Rautiainen","year":"2022","unstructured":"Rautiainen, S., Pantano, M., Traganos, K., Ahmadi, S., Saenz, J., Mohammed, W.M., Martinez Lastra, J.L.: Multimodal interface for human-robot collaboration. Machines 10(10), 957 (2022)","journal-title":"Machines"},{"issue":"7","key":"9394_CR53","doi-asserted-by":"publisher","first-page":"1583","DOI":"10.1007\/s12369-022-00867-0","volume":"14","author":"N Rawal","year":"2022","unstructured":"Rawal, N., Stock-Homburg, R.M.: Facial emotion expressions in human-robot interaction: a survey. Int. J. Soc. Robot. 14(7), 1583\u20131604 (2022)","journal-title":"Int. J. Soc. Robot."},{"issue":"2","key":"9394_CR54","doi-asserted-by":"publisher","first-page":"567","DOI":"10.1016\/j.asoc.2009.08.026","volume":"10","author":"BS Reddy","year":"2010","unstructured":"Reddy, B.S., Basir, O.A.: Concept-based evidential reasoning for multimodal fusion in human-computer interaction. Appl. Soft Comput. 10(2), 567\u2013577 (2010)","journal-title":"Appl. Soft Comput."},{"key":"9394_CR55","doi-asserted-by":"crossref","unstructured":"Rossi, S., Ferland, F., Tapus, A.: User profiling and behavioral adaptation for hri: a survey. Pattern Recognit. Lett. 99:3\u201312. User Profiling and Behavior Adaptation for Human-Robot Interaction (2017)","DOI":"10.1016\/j.patrec.2017.06.002"},{"key":"9394_CR56","doi-asserted-by":"crossref","unstructured":"Rossi, S., Leone, E., Fiore, M., Finzi, A., Cutugno, F. (2013). An extensible architecture for robust multimodal human-robot communication. In: 2013 IEEE\/RSJ International Conference on Intelligent Robots and Systems, pp. 2208\u20132213","DOI":"10.1109\/IROS.2013.6696665"},{"issue":"3","key":"9394_CR57","doi-asserted-by":"publisher","first-page":"211","DOI":"10.1007\/s11263-015-0816-y","volume":"115","author":"O Russakovsky","year":"2015","unstructured":"Russakovsky, O., Deng, J., Su, H., Krause, J., Satheesh, S., Ma, S., Huang, Z., Karpathy, A., Khosla, A., Bernstein, M., Berg, A.C., Fei-Fei, L.: ImageNet large scale visual recognition challenge. Int. J. Comput. Vis. (IJCV) 115(3), 211\u2013252 (2015)","journal-title":"Int. J. Comput. Vis. (IJCV)"},{"issue":"3","key":"9394_CR58","doi-asserted-by":"publisher","first-page":"211","DOI":"10.1007\/s11263-015-0816-y","volume":"115","author":"O Russakovsky","year":"2015","unstructured":"Russakovsky, O., Deng, J., Su, H., Krause, J., Satheesh, S., Ma, S., Huang, Z., Karpathy, A., Khosla, A., Bernstein, M., Berg, A.C., Fei-Fei, L.: ImageNet large scale visual recognition challenge. Int. J. Comput. Vis. (IJCV) 115(3), 211\u2013252 (2015)","journal-title":"Int. J. Comput. Vis. (IJCV)"},{"issue":"6","key":"9394_CR59","doi-asserted-by":"publisher","first-page":"1161","DOI":"10.1037\/h0077714","volume":"39","author":"JA Russell","year":"1980","unstructured":"Russell, J.A.: A circumplex model of affect. J. Pers. Soc. Psychol. 39(6), 1161 (1980)","journal-title":"J. Pers. Soc. Psychol."},{"key":"9394_CR60","doi-asserted-by":"publisher","first-page":"342","DOI":"10.1016\/j.jpsychires.2021.03.043","volume":"138","author":"R Shani","year":"2021","unstructured":"Shani, R., Tal, S., Derakshan, N., Cohen, N., Enock, P.M., McNally, R.J., Mor, N., Daches, S., Williams, A.D., Yiend, J., Carlbring, P., Kuckertz, J.M., Yang, W., Reinecke, A., Beevers, C.G., Bunnell, B.E., Koster, E.H., Zilcha-Mano, S., Okon-Singer, H.: Personalized cognitive training: protocol for individual-level meta-analysis implementing machine learning methods. J. Psychiatr. Res. 138, 342\u2013348 (2021)","journal-title":"J. Psychiatr. Res."},{"key":"9394_CR61","doi-asserted-by":"crossref","unstructured":"Shu, B., Sziebig, G., Pieters, R.: Architecture for safe human-robot collaboration: Multi-modal communication in virtual reality for efficient task execution. In: 2019 IEEE 28th International Symposium on Industrial Electronics (ISIE), 2297\u20132302 (2019)","DOI":"10.1109\/ISIE.2019.8781372"},{"key":"9394_CR62","doi-asserted-by":"publisher","DOI":"10.1016\/j.chb.2020.106627","volume":"117","author":"M Shumanov","year":"2021","unstructured":"Shumanov, M., Johnson, L.: Making conversations with chatbots more personalized. Comput. Hum. Behav. 117, 106627 (2021)","journal-title":"Comput. Hum. Behav."},{"key":"9394_CR63","unstructured":"Simonyan, K., Zisserman, A.: Very deep convolutional networks for large-scale image recognition (2014)"},{"key":"9394_CR64","doi-asserted-by":"publisher","first-page":"50","DOI":"10.1016\/j.specom.2014.05.005","volume":"65","author":"G Skantze","year":"2014","unstructured":"Skantze, G., Hjalmarsson, A., Oertel, C.: Turn-taking, feedback and joint attention in situated human-robot interaction. Speech Commun. 65, 50\u201366 (2014)","journal-title":"Speech Commun."},{"key":"9394_CR65","first-page":"7","volume":"I","author":"M Spezialetti","year":"2020","unstructured":"Spezialetti, M., Placidi, G., Rossi, S.: Emotion recognition for human-robot interaction: Recent advances and future perspectives. Front. Robot. A I, 7 (2020)","journal-title":"Front. Robot. A"},{"issue":"8","key":"9394_CR66","doi-asserted-by":"publisher","first-page":"2046","DOI":"10.1177\/1747021819829012","volume":"72","author":"TM Sutton","year":"2019","unstructured":"Sutton, T.M., Herbert, A.M., Clark, D.Q.: Valence, arousal, and dominance ratings for facial stimuli. Quart. J. Exp. Psychol. 72(8), 2046\u20132055 (2019). (PMID: 30760113)","journal-title":"Quart. J. Exp. Psychol."},{"key":"9394_CR67","doi-asserted-by":"crossref","unstructured":"Thoker, F.M. Gall, J.: Cross-modal knowledge distillation for action recognition (2019)","DOI":"10.1109\/ICIP.2019.8802909"},{"key":"9394_CR68","unstructured":"Tio, A.E.: Face shape classification using inception v3 (2019)"},{"key":"9394_CR69","doi-asserted-by":"crossref","unstructured":"Tulsiani, S. Malik, J.: Viewpoints and keypoints (2014)","DOI":"10.1109\/CVPR.2015.7298758"},{"issue":"2","key":"9394_CR70","doi-asserted-by":"publisher","first-page":"2159","DOI":"10.1007\/s11042-015-3119-y","volume":"76","author":"GK Verma","year":"2016","unstructured":"Verma, G.K., Tiwary, U.S.: Affect representation and recognition in 3d continuous valence\u2013arousal\u2013dominance space. Multimedia Tools Appl. 76(2), 2159\u20132183 (2016)","journal-title":"Multimedia Tools Appl."},{"key":"9394_CR71","doi-asserted-by":"crossref","unstructured":"Wang, J., Tang, Z., Li, X., Yu, M., Fang, Q., Liu, L.: Cross-modal knowledge distillation method for automatic cued speech recognition (2021)","DOI":"10.21437\/Interspeech.2021-432"},{"issue":"2","key":"9394_CR72","doi-asserted-by":"publisher","first-page":"701","DOI":"10.1016\/j.cirp.2019.05.002","volume":"68","author":"L Wang","year":"2019","unstructured":"Wang, L., Gao, R., V\u00e1ncza, J., Kr\u00fcger, J., Wang, X., Makris, S., Chryssolouris, G.: Symbiotic human-robot collaborative assembly. CIRP Ann. 68(2), 701\u2013726 (2019)","journal-title":"CIRP Ann."},{"key":"9394_CR73","unstructured":"Warden, P.: Speech commands: A dataset for limited-vocabulary speech recognition (2018)"},{"key":"9394_CR74","doi-asserted-by":"crossref","unstructured":"Wilde, N., Kuli\u0107, D., Smith, S.L.: Learning user preferences in robot motion planning through interaction. In: 2018 IEEE International Conference on Robotics and Automation (ICRA), 619\u2013626 (2018)","DOI":"10.1109\/ICRA.2018.8460586"},{"key":"9394_CR75","doi-asserted-by":"crossref","unstructured":"Wongvibulsin, S., Frech, T.\u00a0M., Chren, M.-M., Tkaczyk, E.R.: Expanding personalized, data-driven dermatology: Leveraging digital health technology and machine learning to improve patient outcomes. JID Innovations, 100105 (2022)","DOI":"10.1016\/j.xjidi.2022.100105"},{"key":"9394_CR76","doi-asserted-by":"publisher","first-page":"241","DOI":"10.1016\/j.trc.2019.05.042","volume":"105","author":"D Yi","year":"2019","unstructured":"Yi, D., Su, J., Liu, C., Quddus, M., Chen, W.-H.: A machine learning based personalized system for driving state recognition. Transp. Res. Part C Emerg. Technol. 105, 241\u2013261 (2019)","journal-title":"Transp. Res. Part C Emerg. Technol."},{"key":"9394_CR77","doi-asserted-by":"crossref","unstructured":"Zhao, M., Li, T., Alsheikh, M.\u00a0A., Tian, Y., Zhao, H., Torralba, A., Katabi, D.: Through-wall human pose estimation using radio signals. In 2018 IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 7356\u20137365 (2018)","DOI":"10.1109\/CVPR.2018.00768"},{"key":"9394_CR78","doi-asserted-by":"publisher","first-page":"9573","DOI":"10.3390\/s111009573","volume":"11","author":"X Zhao","year":"2011","unstructured":"Zhao, X., Zhang, S.: Facial expression recognition based on local binary patterns and kernel discriminant isomap. Sensors (Basel, Switzerland) 11, 9573\u201388 (2011)","journal-title":"Sensors (Basel, Switzerland)"}],"container-title":["User Modeling and User-Adapted Interaction"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11257-024-09394-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11257-024-09394-1\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11257-024-09394-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,9,25]],"date-time":"2024-09-25T17:09:37Z","timestamp":1727284177000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11257-024-09394-1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,3,22]]},"references-count":78,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2024,9]]}},"alternative-id":["9394"],"URL":"https:\/\/doi.org\/10.1007\/s11257-024-09394-1","relation":{"has-preprint":[{"id-type":"doi","id":"10.21203\/rs.3.rs-2656781\/v1","asserted-by":"object"}]},"ISSN":["0924-1868","1573-1391"],"issn-type":[{"value":"0924-1868","type":"print"},{"value":"1573-1391","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,3,22]]},"assertion":[{"value":"5 March 2023","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"6 January 2024","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"22 March 2024","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors have no relevant financial or non-financial interests to disclose.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}},{"value":"Not applicable","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval"}},{"value":"Not applicable","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent to participate"}},{"value":"All authors have read and agreed to the published version of the manuscript","order":5,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}}]}}