Enhancing User Experience through Emotional Interaction: Determining Users Interests in Online Art Collections using AMARA (Affective Museum of Art Resource Agent)

2021 ◽  
Author(s):  
Sang Joon Park
Keyword(s):  
User Experience ◽  
Art Collections ◽  
Emotional Interaction ◽  
Resource Agent

Research on Emotional Interaction Design of Mobile Terminal Application

2014 ◽  
Vol 989-994 ◽  
pp. 5528-5531
Author(s):  
Xiao Meng Mao
Keyword(s):  
User Experience ◽  
Interaction Design ◽  
Interface Design ◽  
Design Patterns ◽  
Mobile Terminal ◽  
Application Software ◽  
Functional Requirements ◽  
Interactive Mode ◽  
Software Applications ◽  
Emotional Interaction

Discusses the realization of the path of the mobile terminal application software emotional interaction design. Analyzed design features of mobile terminal application software with combined hardware and software features. Analysis of the current features of emotional interaction design software applications. People's basic functional requirements of the mobile terminal application software for rising to the emotional and reflective user experience. Realize the emotional user experience needs improvements of interactive mode; interface design patterns; human-computer interaction applications feedback and deep-rooted experience of the target software features.

scholarly journals A Novel User Emotional Interaction Design Model Using Long and Short-Term Memory Networks and Deep Learning

2021 ◽  
Vol 12 ◽  
Author(s):  
Xiang Chen ◽  
Rubing Huang ◽  
Xin Li ◽  
Lei Xiao ◽  
Ming Zhou ◽  
...  
Keyword(s):  
Deep Learning ◽  
Emotion Recognition ◽  
User Experience ◽  
Interaction Design ◽  
Speech Signal ◽  
Short Term Memory ◽  
Emotional Design ◽  
Short Term ◽  
Term Memory ◽  
Emotional Interaction

Emotional design is an important development trend of interaction design. Emotional design in products plays a key role in enhancing user experience and inducing user emotional resonance. In recent years, based on the user's emotional experience, the design concept of strengthening product emotional design has become a new direction for most designers to improve their design thinking. In the emotional interaction design, the machine needs to capture the user's key information in real time, recognize the user's emotional state, and use a variety of clues to finally determine the appropriate user model. Based on this background, this research uses a deep learning mechanism for more accurate and effective emotion recognition, thereby optimizing the design of the interactive system and improving the user experience. First of all, this research discusses how to use user characteristics such as speech, facial expression, video, heartbeat, etc., to make machines more accurately recognize human emotions. Through the analysis of various characteristics, the speech is selected as the experimental material. Second, a speech-based emotion recognition method is proposed. The mel-Frequency cepstral coefficient (MFCC) of the speech signal is used as the input of the improved long and short-term memory network (ILSTM). To ensure the integrity of the information and the accuracy of the output at the next moment, ILSTM makes peephole connections in the forget gate and input gate of LSTM, and adds the unit state as input data to the threshold layer. The emotional features obtained by ILSTM are input into the attention layer, and the self-attention mechanism is used to calculate the weight of each frame of speech signal. The speech features with higher weights are used to distinguish different emotions and complete the emotion recognition of the speech signal. Experiments on the EMO-DB and CASIA datasets verify the effectiveness of the model for emotion recognition. Finally, the feasibility of emotional interaction system design is discussed.

Assessing User Experience with Crutch Use

2011 ◽  
Author(s):  
Christina Harrington ◽  
Sharon Joines
Keyword(s):  
User Experience

Conventions and temporal differences in painted faces: A study of posture and color distribution

2020 ◽  
Vol 2020 (11) ◽  
pp. 267-1-267-8
Author(s):  
Mitchell J.P. van Zuijlen ◽  
Sylvia C. Pont ◽  
Maarten W.A. Wijntjes
Keyword(s):  
Scientific Community ◽  
Human Face ◽  
Art Galleries ◽  
Art Collections ◽  
Color Distribution ◽  
Scientific Domain ◽  
The Face ◽  
And Gender ◽  
Changes Over Time ◽  
Over Time

The human face is a popular motif in art and depictions of faces can be found throughout history in nearly every culture. Artists have mastered the depiction of faces after employing careful experimentation using the relatively limited means of paints and oils. Many of the results of these experimentations are now available to the scientific domain due to the digitization of large art collections. In this paper we study the depiction of the face throughout history. We used an automated facial detection network to detect a set of 11,659 faces in 15,534 predominately western artworks, from 6 international, digitized art galleries. We analyzed the pose and color of these faces and related those to changes over time and gender differences. We find a number of previously known conventions, such as the convention of depicting the left cheek for females and vice versa for males, as well as unknown conventions, such as the convention of females to be depicted looking slightly down. Our set of faces will be released to the scientific community for further study.

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