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Emotion-aware Chat Machine: Automatic Emotional Response Generation for Human-like Emotional Interaction [article]

Wei Wei, Jiayi Liu, Xianling Mao, Guibing Guo, Feida Zhu, Pan Zhou, Yuchong Hu
2021 arXiv   pre-print
The consistency of a response to a given post at semantic-level and emotional-level is essential for a dialogue system to deliver human-like interactions.  ...  responses with appropriately expressed emotions.  ...  CONCLUSION In this paper, we propose an emotion-aware chat machine (EACM) to address the emotional response generation problem, which is composed of an emotion selector and a response generator.  ... 
arXiv:2106.03044v1 fatcat:c32tcpnjcrhbhioowa4teeydcm

Towards Socialized Machines: Emotions and Sense of Humour in Conversational Agents [chapter]

Michal Ptaszynski, Pawel Dybala, Shinsuke Higuhi, Wenhan Shi, Rafal Rzepka, Kenji Araki
2010 Web Intelligence and Intelligent Agents  
Therefore, if humour enhances the interaction between humans, a similar effect should be obtained in interaction with machines.  ...  C) Emotion Since one of the agents was using humorous responses we also checked whether the jokes influenced the human-computer interaction.  ...  Towards Socialized Machines: Emotions and Sense of Humour in Conversational Agents, Web Intelligence and Intelligent Agents, Zeeshan-Ul-Hassan Usmani (Ed.), ISBN: 978-953-7619-85-5, InTech, Available from  ... 
doi:10.5772/8384 fatcat:ep7ibksscjdkja6qiuc4a6q2ym

Conditional Text Generation for Harmonious Human-Machine Interaction [article]

Bin Guo, Hao Wang, Yasan Ding, Wei Wu, Shaoyang Hao, Yueqi Sun, Zhiwen Yu
2020 arXiv   pre-print
The automatically generated text is becoming more and more fluent so researchers begin to consider more anthropomorphic text generation technology, that is the conditional text generation, including emotional  ...  In recent years, with the development of deep learning, text generation technology has undergone great changes and provided many kinds of services for human beings, such as restaurant reservation and daily  ...  CONCLUSION We have made a systematic review of the research trends of conditional text generation (c-TextGen).  ... 
arXiv:1909.03409v2 fatcat:s2zfmwxtubgwjks4luoby6vdoq

Toward Machines With Emotional Intelligence [chapter]

Rosalind W. Picard
2008 The Science of Emotional IntelligenceKnowns and Unknowns  
Machines are now being given the ability to sense and recognize expressions of human emotion such as interest, distress, and pleasure, with the recognition that such communication is vital for helping  ...  empathetic or otherwise emotionally intelligent.  ...  Acknowledgments I would like to thank Shaundra Bryant Daily for helpful comments on this manuscript.  ... 
doi:10.1093/acprof:oso/9780195181890.003.0016 fatcat:hcgd24wdirhjpkpe7rot25s3ry

Human computing and machine understanding of human behavior

Maja Pantic, Alex Pentland, Anton Nijholt, Thomas Huang
2006 Proceedings of the 8th international conference on Multimodal interfaces - ICMI '06  
If this prediction is to come true, then next generation computing, which we will call human computing, should be about anticipatory user interfaces that should be human-centered, built for humans based  ...  They should transcend the traditional keyboard and mouse to include natural, human-like interactive functions including understanding and emulating certain human behaviors such as affective and social  ...  of social networks formed of humans and computers (like in the case of virtual worlds), in their current form, they are not appropriate for general anticipatory interfaces.  ... 
doi:10.1145/1180995.1181044 dblp:conf/icmi/PanticPNH06 fatcat:wyix2qgyrrfczfcthifm3gzfcu

Chatbots: History, technology, and applications

Eleni Adamopoulou, Lefteris Moussiades
2020 Machine Learning with Applications  
It aims to organize critical information that is a necessary background for further research activity in the field of chatbots.  ...  After we present a complete categorization system, we analyze the two essential implementation technologies, namely, the pattern matching approach and machine learning.  ...  However, ALICE did not have intelligent features and could not generate human-like answers expressing emotions or attitudes.  ... 
doi:10.1016/j.mlwa.2020.100006 fatcat:ezeuv56hizf3rfbo2ekb2yksiy

Suicidal Ideation Detection: A Review of Machine Learning Methods and Applications [article]

Shaoxiong Ji and Shirui Pan and Xue Li and Erik Cambria and Guodong Long and Zi Huang
2020 arXiv   pre-print
engineering or deep learning for automatic detection based on online social contents.  ...  Current suicidal ideation detection methods include clinical methods based on the interaction between social workers or experts and the targeted individuals and machine learning techniques with feature  ...  To enable timely intervention for suicidal thoughts, automatic response generation becomes a promising technical solution.  ... 
arXiv:1910.12611v2 fatcat:63z4uvh5zrgyzb2bawtlbuo34m

Cybersex with human- and machine-cued partners: Gratifications, shortcomings, and tensions

Jaime Banks, Joris Van Ouytsel
2020 Technology, Mind, and Behavior  
as a human or a machine.  ...  Multimethod analysis suggests there may be no difference in gratifications from sex chat with ostensible machine versus human partners; however, participants seem to experience tensions between the gratifications  ...  As social machines become more human-like in appearance, functioning, and/or behavior, the potential for humans and machines to cooperatively generate meaning through interaction (Guzman, 2018) may include  ... 
doi:10.1037/tmb0000008 fatcat:g5q7wfn7yfeqfkwrubp2ebkh5m

A Thief among Us: The Use of Finite-State Machines to Dissect Insider Threat in Cloud Communications

Shuyuan Mary Ho, Hwajung Lee
2012 Journal of Wireless Mobile Networks, Ubiquitous Computing, and Dependable Applications  
Specifically, the authors adopted a finite-state machine (FSM) approach to analyzing patterns of a group's emotional states in order to understand how members collectively distinguish insider betrayal  ...  through computer-mediated interactions, social connectivity and coordination.  ...  The first author wishes to thank Conrad Metcalfe for his editing assistance.  ... 
doi:10.22667/jowua.2012.03.31.082 dblp:journals/jowua/HoL12 fatcat:htfvefxg45fuhhzzlcgf66xlqm

Can machines talk? Comparison of Eliza with modern dialogue systems

Huma Shah, Kevin Warwick, Jordi Vallverdú, Defeng Wu
2016 Computers in Human Behavior  
More than one hundred male and female participants with 1 st or non-1 st English language, age range 13-64, interacted with the systems over the Internet scoring each for conversation ability.  ...  Embedded on the web affording round-the-clock interaction the nature of artificial dialogue systems is evolving as these systems learn from the way humans converse.  ...  We would also like to thank the developers for embedding their conversation systems on special websites across the Internet and making them available to testers throughout 2012 for this experiment.  ... 
doi:10.1016/j.chb.2016.01.004 fatcat:gpyiwmrrjvgy3iciegmawwuhdq

Towards Automatic & Personalised Mobile Health Interventions: An Interactive Machine Learning Perspective [article]

Ahmed Fadhil
2018 arXiv   pre-print
In this paper, we introduce an application of interactive machine learning (iML) in a telemedicine system, to enable automatic and personalised interventions for lifestyle promotion.  ...  We then illustrate the interactive machine learning process design.  ...  The inherent coupling of the human and machine in interactive machine learning underscores the need for collaboration across the fields of human-computer interaction and machine learning.  ... 
arXiv:1803.01842v1 fatcat:jkd4sv3dgffr7ag6aigh4xkr7a

Working with Machines

Min Kyung Lee, Daniel Kusbit, Evan Metsky, Laura Dabbish
2015 Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems - CHI '15  
In these work settings, human jobs are assigned, optimized, and evaluated through algorithms and tracked data.  ...  Software algorithms are changing how people work in an ever-growing number of fields, managing distributed human workers at a large scale.  ...  We thank Su Baykal for helping us collect and analyze data, and the anonymous reviewers for their feedback that improved the paper.  ... 
doi:10.1145/2702123.2702548 dblp:conf/chi/LeeKMD15 fatcat:afb2rh7yunbhbdzxs7as3jxaum

A cognitively based approach to affect sensing from text

Mostafa Al Masum Shaikh, Prendinger Helmut, Mitsuru Ishizuka
2006 Proceedings of the 11th international conference on Intelligent user interfaces - IUI '06  
In particular we want to create a formal model that can not only "understand" what emotions people wrap with their textual messages, but also can make automatic empathic response with respect to the emotional  ...  interaction.  ...  generate an empathic reply or response with respect to the emotional state detected (e.g. in a machine chat for e-learning or online counseling; or automatic reply of customer feedback etc.).  ... 
doi:10.1145/1111449.1111518 dblp:conf/iui/ShaikhHI06 fatcat:4nvlpk3f6vgtzhkeuhtsxgmfwu

COVID-19 Tweets Textual Analytics Using Machine Learning Classification for Fear Sentiment

2020 International Journal of Advanced Trends in Computer Science and Engineering  
In order to increase user accessibility it present to aggregator related COVID-19 microblogging message into the cluster and automatically allocate them semantically meaningful labels.  ...  However, a typical features of COVID-19 microblogging messages is that they are much shorter than standard text document these messages provide insufficient terms of information for capturing semantic  ...  In order to solve this issue, for automatic learning, extraction and analysis, many machine Learning techniques and Deep Learning models are being proposed.  ... 
doi:10.30534/ijatcse/2020/221952020 fatcat:tvlslsmkubfsnnbov7ox3pmma4

Beyond Social Media Analytics: Understanding Human Behaviour and Deep Emotion using Self Structuring Incremental Machine Learning [article]

Tharindu Bandaragoda
2020 arXiv   pre-print
Secondly for the slow-paced social data, a suite of new machine learning and natural language processing techniques were developed to automatically capture self-disclosed information of the individuals  ...  such as demographics, emotions and timeline of personal events.  ...  It extracts information encapsulated in free-text discussions of OSG using a suite of machine learning, natural language processing and emotion analysis techniques and automatically generate individual  ... 
arXiv:2009.09078v1 fatcat:izo3eyjc4vdo3jnttt7omvsv5q
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