scholarly journals Introduction to the Special Issue on Affective Computing for Large-scale Heterogeneous Multimedia Data

2020 ◽  
Vol 15 (3s) ◽  
pp. 1-2
Keyword(s):  
Affective Computing ◽  
Large Scale ◽  
Multimedia Data ◽  
Special Issue

scholarly journals Introduction to the Special Issue on MMAC: Multimodal Affective Computing of Large-Scale Multimedia Data

2021 ◽  
Vol 28 (2) ◽  
pp. 8-10
Author(s):  
Sicheng Zhao ◽  
Min Xu ◽  
Qingming Huang ◽  
Bjorn W. Schuller
Keyword(s):  
Affective Computing ◽  
Large Scale ◽  
Multimedia Data ◽  
Special Issue

scholarly journals Affective Computing for Large-scale Heterogeneous Multimedia Data

2020 ◽  
Vol 15 (3s) ◽  
pp. 1-32
Author(s):  
Sicheng Zhao ◽  
Shangfei Wang ◽  
Mohammad Soleymani ◽  
Dhiraj Joshi ◽  
Qiang Ji
Keyword(s):  
Affective Computing ◽  
Large Scale ◽  
Multimedia Data

scholarly journals Guest Editorial: Special Issue on Large-Scale Wireless-Powered Networks With Backscatter Communications

2020 ◽  
Vol 1 ◽  
pp. 1961-1964
Author(s):  
Sami Muhaidat ◽  
Paschalis C. Sofotasios ◽  
Kaibin Huang ◽  
Muhammad Ali Imran ◽  
Zhiguo Ding ◽  
...  
Keyword(s):  
Large Scale ◽  
Guest Editorial ◽  
Special Issue ◽  
Editorial Special Issue

scholarly journals Investigating the Relationship Between Emotion Recognition Software and Usability Metrics

i-com ◽  
2020 ◽  
Vol 19 (2) ◽  
pp. 139-151
Author(s):  
Thomas Schmidt ◽  
Miriam Schlindwein ◽  
Katharina Lichtner ◽  
Christian Wolff
Keyword(s):  
Emotion Recognition ◽  
Regression Models ◽  
Affective Computing ◽  
Large Scale ◽  
General Purpose ◽  
Thinking Aloud ◽  
Continue Research ◽  
Usability Metrics ◽  
Recognition Software ◽  
The Relationship

AbstractDue to progress in affective computing, various forms of general purpose sentiment/emotion recognition software have become available. However, the application of such tools in usability engineering (UE) for measuring the emotional state of participants is rarely employed. We investigate if the application of sentiment/emotion recognition software is beneficial for gathering objective and intuitive data that can predict usability similar to traditional usability metrics. We present the results of a UE project examining this question for the three modalities text, speech and face. We perform a large scale usability test (N = 125) with a counterbalanced within-subject design with two websites of varying usability. We have identified a weak but significant correlation between text-based sentiment analysis on the text acquired via thinking aloud and SUS scores as well as a weak positive correlation between the proportion of neutrality in users’ voice and SUS scores. However, for the majority of the output of emotion recognition software, we could not find any significant results. Emotion metrics could not be used to successfully differentiate between two websites of varying usability. Regression models, either unimodal or multimodal could not predict usability metrics. We discuss reasons for these results and how to continue research with more sophisticated methods.

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