Emotions are psychophysiological processes that are sparked by both conscious and unconscious perceptions of things and events. Mood, motivation, temperament, and personality are frequently linked to emotions. Human-machine interaction will see the creation of systems that can recognize and interpret human emotions in a range of ways as computers and computer-based applications get more advanced and pervasive in people's daily lives. More sympathetic and customized relationships between humans and machines can result from efficient emotion recognition in human-machine interactions. Emotion recognition systems are able to modify their responses and user experience based on the analysis of interpersonal communication signals. The ability of virtual assistants to respond emotionally more effectively, the ability to support mental health systems by identifying users' emotional states, the improvement of customer support interactions with emotionally responsive Chabots, and the enhancement of human-robot collaboration are just a few examples of real-world applications. Reviewing the interpersonal communication elements of the emotional interaction models that are now in use is the aim of this chapter.
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Human-computer interactions have advanced beyond basic functioning in the current digital era, placing an emphasis on emotional resonance and empathy. AI-powered emotional intelligence (AEI) is a revolutionary method of bridging the human-machine divide. AEI transforms user experiences by endowing technologies with the ability to recognize, comprehend, and react to human emotions. Artificial Emotion Intelligence (AEI) allows computers to understand human emotions remarkably well by using sophisticated facial expression, speech, and contextual cue interpretation. A study pointed deeper relationships between humans and robots are fostered through the usage of this technology, which makes interactions more meaningful, personalized, and intuitive (Weiss & Spiel, 2022). AEI has the potential to improve people's lives through empathic and responsive computing, revolutionizing a range of industries such as healthcare and customer service to education and entertainment.
The quality of interpersonal communication in digital environments is being improved by machines that can recognize and understand human emotions thanks to the development of emotion recognition technology, which is drastically changing human-machine interaction. It is essential for the advancement of research in this segment to comprehend the theoretical underpinnings, technological developments, and ramifications of these advancements. Under the umbrella term “affective computing,” research on the function of emotions during user-interaction with interactive systems has grown in the past few years (Picard 1997). According to Gratch and Marsella (2004), the basic tenet of the theory is that “incorporating” emotions into interactive systems would improve system responses and, as a result, allow system users to respond in ways that are more realistic (de Melo, Carnevale, and Gratch 2012, Krämer et al. 2013).
In the psychology of human robot interaction (HRI) perspective, emotion recognition is essential since it has a significant impact on the dynamics and efficacy of these interactions (Gervasi et al., 2023). Gaining the benefits of social intelligence and empathy in user interactions requires robots to be emotionally intelligent and capable of recognizing and interpreting human emotions. Emotion recognition has several potential uses in the fields of psychology and Human–Computer Interaction (HCI). An individual's emotions are fundamental to their daily choices and overall wellbeing. Affect and emotion play important roles in human existence. People's thoughts and actions are influenced by their emotions, particularly when they are interacting with other people.
The voice, face, and full body all provide emotional cues, which are essential pieces of information for interpersonal communication. Understanding emotions is essential to both human–machine and interpersonal communication. Although most earlier research on the subject concentrated on a small number of actions, body expression may have a role in emotion identification. Furthermore, the majority of earlier research's emotions were acted out, leading to non-natural motion that has no practical application. A study pointed, emotion is crucial for identifying people's comprehension of motivations and behaviors, making it a crucial component in human–machine interaction. Scholars have also identified emotions as the “translation” of non-expressive verbalization or voice modulation, facial expression, or body language (Riemer, Joseph, Lee, and Riemer, 2023). This chapter focuses on a review in interpersonal communication perspective in the emotion recognition in human-machine interaction. Some directions by applying the theoretical frameworks, applications and challenges of emotion recognition in human-machine interaction as well as future directions.