Using virtual reality to investigate the emergence of gaze conventions in interpersonal coordination

Gaze plays a central role in regulating turn-taking, but it is currently unclear whether the turn-taking signals of eye gaze are static and fixed, or whether they can be negotiated by participants during interaction. To address this question, participants play a novel collaborative task, in virtual reality. The task is played by 3 participants, and is inspired by games such as Guitar he-ro, Rock Band, Beat Saber, and Dance-Dance Revolution. Crucially, the par-ticipants are not allowed to use natural language – they may only communi-cate by looking at each other. Solving the task requires that participants boot-strap a communication system, solely through using their gaze patterns. The results show that participants rapidly conventionalise idiosyncratic routines for coordinating the timing and sequencing of their gaze patterns. This sug-gests that the turn-taking function of eye-gaze can be flexibly negotiated by interlocutors during interaction

Using virtual reality to investigate the emergence of gaze conventions in interpersonal coordination

Gaze plays a central role in regulating turn-taking, but it is currently unclear whether the turn-taking signals of eye gaze are static and fixed, or whether they can be negotiated by participants during interaction. To address this question, participants play a novel collaborative task, in virtual reality. The task is played by 3 participants, and is inspired by games such as Guitar hero, Rock Band, Beat Saber, and Dance-Dance Revolution. Crucially, the participants are not allowed to use natural language – they may only communicate by looking at each other. Solving the task requires that participants bootstrap a communication system, solely through using their gaze patterns. The results show that participants rapidly conventionalise idiosyncratic routines for coordinating the timing and sequencing of their gaze patterns. This suggests that the turn-taking function of eye-gaze can be flexibly negotiated by interlocutors during interaction.</p

The CLIN27 Shared Task: Translating Historical Text to Contemporary Language for Improving Automatic Linguistic Annotation

The CLIN27 shared task evaluates the effect of translating historical text to modern text with the goal of improving the quality of the output of contemporary natural language processing tools applied to the text. We focus on improving part-of-speech tagging analysis of seventeenth-century Dutch. Eight teams took part in the shared task. The best results were obtained by teams employing character-based machine translation. The best system obtained an error reduction of 51% in comparison with the baseline of tagging unmodified text. This is close to the error reduction obtained by human translation (57%).status: publishe

The CLIN27 Shared Task : Translating Historical Text to Contemporary Language for Improving Automatic Linguistic Annotation

The CLIN27 shared task evaluates the effect of translating historical text to modern text with the goal of improving the quality of the output of contemporary natural language processing tools applied to the text. We focus on improving part-of-speech tagging analysis of seventeenth-century Dutch. Eight teams took part in the shared task. The best results were obtained by teams employing character-based machine translation. The best system obtained an error reduction of 51% in comparison with the baseline of tagging unmodified text. This is close to the error reduction obtained by human translation (57%)