Swee Lan See

Making Social Robots More Attractive: The Effects of Voice Pitch, Humor and Empathy

In this paper we explore how simple auditory/verbal features of the spoken language, such as voice characteristics (pitch) and language cues (empathy/humor expression) influence the quality of interaction with a social robot receptionist. For our experiment two robot characters were created: Olivia, the more extrovert, exuberant, and humorous robot with a higher voice pitch and Cynthia, the more introvert, calmer and more serious robot with a lower voice pitch. Our results showed that the voice pitch seemed to have a strong influence on the way users rated the overall interaction quality, as well as the robot’s appeal and overall enjoyment. Further, the humor appeared to improve the users’ perception of task enjoyment, robot personality and speaking style while the empathy showed effects on the way users evaluated the robot’s receptive behavior and the interaction ease. With our study, we would like to stress in particular the importance of voice pitch in human robot interaction and to encourage further research on this topic.

Investigation of social media on depression

With rapid technological advancement, many have questioned the benefits and side effects of social media on a users psychological health. Research from the western communities found a strong correlation between social media and depression rate. This research further affirms this finding in the Asian counterpart. A study was carried out in Singapore to determine the relationship of social media usage and depression in Asian individuals of different genders and age groups. Our findings show that the higher the usage of social media, the higher the risk of depression, with teenage girls being subjected to the highest risk. An early depression detector is proposed to track and control this risk factor of social media usage.

Proposal of a depression detector

Rapid advancements in technology, coupled with the increasingly widespread usage of social media, has brought about various impacts on our psychological health. Past research has been conducted on Singaporeans and ascertained the relationship between frequency of social media usage and depression levels in teenage girls. This research aims to investigate the relationship between depression and voice characteristics namely pitch, loudness and number of pauses, so as to determine markers for depression. The markers were then incorporated into a smartphone game designed to detect depression level through voice analysis. The likelihood of an individual suffering from depression was found to increase with loudness and frequency of pauses and to decrease with the frequency of an individuals voice. A mock up of the smartphone application was created on Justinmind and Powerpoint.

“I Know U” – A Proposed VUI Design for Improving User Experience in HRI

A new aspect of the VUI design for improving user experience in human-robot interaction is proposed. By leveraging on behavioral analysis, we attempt to identify user’s ethnic group from his speech. A preliminary study on Chinese nationals, Singaporean, and Japanese showed that different ethnic group display different speech pattern. However, across ethnic groups, the spoken style of users with same personality does not differ much. Within each ethnic group, speech pattern of users with different personality can be different. We affirmed that personality influences speech and it can be determined in spoken communication.

Socializing with Olivia, the youngest robot receptionist outside the lab

In this paper we present the evaluation results of an exploratory study performed in an open environment with the robot receptionist Olivia. The main focus of the study was to analyze relationships between the robots social skills and the perceived overall interaction quality, as well as to determine additional important interaction quality features with potential general validity. Our results show positive correlations between the investigated factors, as the ability to socialize with humans achieved the second highest correlation with the perceived interaction quality. One of the most relevant functional aspects for the interaction quality was found to be the ability to respond fast. Performance abilities, such as speech or object recognition were, surprisingly, considered less important. The voice pleasantness was regarded as one of the most important non-functional aspects being ranked higher than a nice physical appearance.

Towards Better Human Robot Interaction: Understand Human Computer Interaction in Social Gaming Using a Video-Enhanced Diary Method

This paper presents findings from a descriptive research on social gaming. A video-enhanced diary method was used to understand the user experience in social gaming. From this experiment, we found that natural human behavior and gamer’s decision making process can be elicited and speculated during human computer interaction. These are new information that we should consider as they can help us build better human computer interfaces and human robotic interfaces in future.

Adaptive UI for Enhanced Music Experience

With the increasing popularity of digital music player applications, it is not difficult to find such app used by smartphone users. However, the current user interface (UI) design of these mobile music apps is often too rigid and unable to engage users for prolonging pleasurable entertainment. There is, therefore, a need to improve the aesthetics of this UI to enhance user experience and to keep and sustain customer loyalty. This paper will share feedback from 50 participants on existing music player applications’ UI design, and explore the relationship between user’s personality and preference (such as music genre) for better UI design of mobile music app. The research aims to predict the trend of these variables and would like to propose a customizable UI design of a mobile music app prototype.

Affective Response to Photographs of Natural Landscapes Based on OCEAN Model

The Attention Restoration Theory (Kaplan in J Environ Psychol 15:169–182, 1995 [2]) and the psychological stress reduction theory (Ulrich et al. in J Environ Psychol 11:201–230, 1991 [3]) show that natural landscapes generally stimulate positive emotions. However, Gray’s biopsychological theory of personality suggested different personalities process environmental stimuli differently, leading to varying levels of or completely different emotions. Thus, current emotion tags to landscapes are likely inaccurate, as they lack the consideration of personality type. This study investigates the relationship between the emotions experienced and personality types. 50 participants aged 10–80 years were invited to watch a slideshow of landscapes. Subsequently, they were recorded reading a short passage. To assess participants’ emotions, the voice recordings were processed using PRAAT, a scientific software for analysis of phonetics in speech, and a modified version of the Profile of Mood States (POMS). The results provided the foundation to more accurate tagging programmes linking photographs of natural landscapes with emotions evoked in different personalities.

Language e-Learning and Music Appreciation

Globalisation and the rise in mobile technology led to the rise of language e-learning for leisure and work purposes. However, current language apps in the market often lack adaptation to relevant gamification and pedagogies for learners with integrative and instrumental motivation. Consequently, learners lose interest as the apps fail to engage them and fulfill their learning objectives. Moreover, the appreciation of the underlying cultures in music appreciation has not been fully understood. It was discovered that music and language have neurological links, and when introduced simultaneously, benefits both language and music education. Sadly, the lack of music appreciation and language abilities could be attributed to social stratification. Possession of such cultural capital can exacerbate social inequality by causing the Matthew effect, triggering the poverty trap. Therefore, we propose the ‘Polyglotism’ prototype to devise a more effective e-learning strategy and mitigate social inequality through free access to language and music education.

Understanding Users by Their D.I.S.C. Personality through Interactive Gaming

A key component of improving human-computer interaction is through the matching of users with their preferred computer interfaces and interaction styles. Understanding the users better would result in a customized gaming experience, leading to sustained user engagement. In this paper, we develop an alternative tool to aid in the measurement of the D.I.S.C. personality styles of users in the form of an interactive game. Through this game, we aim to predict the personality type of the gamer, from which invaluable insights about each type of gamer can be elicited.