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Contemporary politics is filled with anxiety about the survival of democracy—particularly within a framework pitting liberal representative democracy against authoritarianism. In times of anxiety about authoritarianism, Western artists repeatedly return to a masterpiece of relatively early cinema: Robert Weine’s silent film Das Cabinet des Dr. Caligari, or The Cabinet of Dr. Caligari. This essay examines three twenty-first century adaptations: David Lee Fisher’s 2005 remake of the film; James Morrow’s 2017 novel, The Asylum of Dr. Caligari; and Georgie Bailey’s 2022 play Caligari. I argue that while the direct politico-cultural anxieties of Weine’s film have often been overstated, the emergence of adaptations during periods of heightened concern about authoritarianism reflects a deep-seated reception of the film as anticipating autocratic governance. However, for all its fears about power, control, and the loss of self-determination, Weine’s movie also contains the seeds of liberation. Cesare ultimately sacrifices his own life rather than murdering Jane. And it is this gesture that the adaptations examined here seek—a gesture of resistance. The sleepwalker can awaken and assert a form of just resistance in the world, even if the penalties are steep. Full article

Human-to-human communication via the computer is mainly carried out using a keyboard or microphone. In the field of virtual reality (VR), where the most immersive experience possible is desired, the use of a keyboard contradicts this goal, while the use of a microphone is not always desirable (e.g., silent commands during task-force training) or simply not possible (e.g., if the user has hearing loss). Data gloves help to increase immersion within VR, as they correspond to our natural interaction. At the same time, they offer the possibility of accurately capturing hand shapes, such as those used in non-verbal communication (e.g., thumbs up, okay gesture, …) and in sign language. In this paper, we present a hand-shape recognition system using Manus Prime X data gloves, including data acquisition, data preprocessing, and data classification to enable nonverbal communication within VR. We investigate the impact on accuracy and classification time of using an outlier detection and a feature selection approach in our data preprocessing. To obtain a more generalized approach, we also studied the impact of artificial data augmentation, i.e., we created new artificial data from the recorded and filtered data to augment the training data set. With our approach, 56 different hand shapes could be distinguished with an accuracy of up to 93.28%. With a reduced number of 27 hand shapes, an accuracy of up to 95.55% could be achieved. The voting meta-classifier (VL2) proved to be the most accurate, albeit slowest, classifier. A good alternative is random forest (RF), which was even able to achieve better accuracy values in a few cases and was generally somewhat faster. outlier detection was proven to be an effective approach, especially in improving the classification time. Overall, we have shown that our hand-shape recognition system using data gloves is suitable for communication within VR. Full article

The noun–verb distinction has long been considered a fundamental property of human language, and has been found in some form even in the earliest stages of language emergence, including homesign and the early generations of emerging sign languages. We present two experimental studies that use silent gesture to investigate how noun–verb distinctions develop in the manual modality through two key processes: (i) improvising using novel signals by individuals, and (ii) using those signals in the interaction between communicators. We operationalise communicative interaction in two ways: a setting in which members of the dyad were in separate booths and were given a comprehension test after each stimulus vs. a more naturalistic face-to-face conversation without comprehension checks. There were few differences between the two conditions, highlighting the robustness of the paradigm. Our findings from both experiments reflect patterns found in naturally emerging sign languages. Some formal distinctions arise in the earliest stages of improvisation and do not require interaction to develop. However, the full range of formal distinctions between nouns and verbs found in naturally emerging language did not appear with either improvisation or interaction, suggesting that transmitting the language to a new generation of learners might be necessary for these properties to emerge. Full article