The goal of this study was to determine whether learning processes and outcomes are affected by the emotional tone of the computer-generated voice in a narrated slideshow. In a between-subjects design, participants viewed a narrated slideshow on lightning formation involving a computer-generated female (Experiment 1) or male voice (Experiment 2) that displayed happy, content, angry, or sad emotion. On subsequent surveys and post-tests, students could recognize positive or negative emotions conveyed by the female voice but not the male voice. The emotional tone of the instructor’s voices had minimal impact on students’ ratings of felt emotion during learning, ratings of social connection with the instructor, or scores on retention and transfer tests of learning outcome. The findings highlight the limitations of computer-generated voices to convey emotions that trigger affective, social, and cognitive processes when an onscreen instructor is absent, thereby suggesting a boundary condition for the cognitive-affective model of e-learning.

An animated agent’s believability, often defined as “the illusion of life,” has many facets, including the agent’s appearance, movements, and user interactions. Considering that human facial expressions are often not symmetrical, evaluating how facial expression asymmetries affect believability in animated agents would provide valuable insights for researchers and artists. Our research focused on facial movements and examined the impact of three dynamic facial asymmetries on users’ perception of the agent’s believability, appeal, and naturalness. Our research involved three studies: 1) a preliminary study in which we determined the maximum values to base asymmetry levels, 2) a study in which we identified what level of asymmetry yields the most perceived believability for each asymmetry location, and 3) a study in which we determined what effects different combinations of asymmetries have on perceived believability, appeal, and naturalness. The findings confirmed the effect of dynamic facial asymmetry on the agents’ perceived believability, appeal, and naturalness. Furthermore, our research suggests that including one or a combination of asymmetric eyebrow, mouth, or eyelid motions increases the agents’ perceived believability, appeal, and naturalness.

We examined the effects of virtual characters’ body type and voice pitch on perceived audio-visual correspondence and believability. For our within-group study (N = 72), we developed nine experimental conditions using a 3 (body type: ectomorph vs. mesomorph vs. endomorph body types) × 3 (voice pitch: low vs. medium vs. high fundamental frequency [F0]) design. We found statistically significant main effects from voice pitch and statistically significant interaction effects between a virtual character’s body type and voice pitch on both the level of perceived audio-visual correspondence and believability of female and male virtual characters. For female virtual characters, we also observed an additional statistically significant main effect from body type and a statistically significant interaction effect between the participant’s biological sex and the virtual character’s voice pitch on both perceived audio-visual correspondence and believability. Moreover, the results show that perceived believability is highly correlated to perceived audio-visual correspondence. Our findings have important practical implications in applications where the virtual character is meant to be an emotional or informational guide that requires some level of perceived believability, as the findings suggest that it is possible to enhance the perceived believability of the virtual characters by generating appropriate voices through pitch manipulation of existing voices.

The current common color image encryption algorithms applying “scrambling-diffusion” have some problems, such as the small key space, the cumbersome encryption process, and the security vulnerability. Aiming at these problems, this paper proposes a new color image encryption algorithm based on the hyperchaotic system and applying “transforming-scrambling-diffusion” model. Before scrambling, in accordance with the plaintext itself attributes, the number of iterations was calculated, all the pixel values of color image were transformed into gray code iteratively, and then the chaotic sequence was generated from the four-dimensional hyperchaotic system. Pixel matrix after gray code transformation was converted to one-dimensional matrix. The chaotic sequence was sorted and the one-dimensional matrix was changed positions correspondingly to complete the whole domain scrambling. And then, bit-operation was executed for image diffusion. The ciphertext can be obtained by matrix transformation. The key sensitivity, histogram, information entropy, correlation, and other evaluation indexes were calculated and analyzed through the simulation experiment. Compared with other algorithms, it can be proved that the encryption algorithm has the strong antiattack ability.