## 3 Methods
### Dataset  
The dataset used in this study was derived from VR communication experiments conducted in our previous work [15]. Figure 1 illustrates the overall workflow of the experiment. The experiment involved 24 participants, evenly distributed between males (12) and females (12), aged between 22 and 30, with most being graduate students. Of these participants, 13 had prior experience with VR, while 11 did not. To minimize potential biases caused by varying levels of VR familiarity, a pre-experiment was conducted for participants without VR experience to familiarize them with the VR equipment and virtual environment before the formal experiment. The experiment was conducted in a virtual meeting room environment (as shown in Figure 2). Previous research has demonstrated that VR environments can influence users in a manner similar to physical environments [50; 51; 52]. Based on this, we selected a conventional and formal virtual environment to encourage participants to focus on the experimental tasks [53]. In the virtual environment, each participant was represented by a simplified avatar consisting of a head, upper torso, and hands. To control for any additional effects of avatar design on communication [54; 55], all participants were provided with identical avatars to ensure consistency of experimental variables. The experimental task was conducted in groups, with participants engaging in a social game called \"Two Truths and a Lie\" [56]. This type of icebreaker game was chosen because it fosters a relaxed and lively discussion atmosphere, allowing participants to naturally integrate into the discussion and encouraging the expression of speaking intentions [57; 58]. During the experimental implementation phase, all participants were randomly divided into six groups, each consisting of four members, with an equal distribution of two males and two females in each group to ensure gender balance. Each group used Meta Quest 2 headsets to enter the virtual meeting room, where they communicated for approximately 15 min. In the virtual space, participants' avatars could move and rotate freely using the joystick on handheld controllers, with motions tracked to reflect participants' physical movements. For data collection phase, we recorded VR tracking data throughout the interaction, including the position, rotation, velocity, acceleration, angular velocity and angular acceleration of participants' avatars. Additionally, the discussion process was fully recorded  
Figure 1: Workflow of the VR communication experiment. Figure 2: Virtual environment used for the experiment (**A**). Participants engaged in discussions within this environment (**B**). using the devices' built-in screen recording feature. These recordings were used to annotate speech events by segmenting speech into inter-pausal units (IPUs) using a 200 ms pause threshold [59; 60]. Speech intervals exceeding this threshold were considered separate speech units. To capture moments when participants attempted to acquire speaking turns, we employed a retrospective cue-based approach to collect speaking intention tags. After the experiment, participants reviewed the recorded discussions and annotated the specific timestamps when they began expressing speaking intentions. During annotation, participants referred to social signals they displayed, such as audible lip-smacking or tongue-clicking sounds, posture adjustments, deep breaths, or noticeable mouth movements [14; 26], to determine the moments when they clearly exhibited speaking intentions and attempted to gain speaking turns. Notably, speaking intentions are not always directly linked to actual speaking behavior. Some speaking intentions failed to result in speech, possibly because participants abandoned their attempts due to a lack of suitable opportunities. Conversely, some speaking behaviors might be driven by group pressure rather than explicit speaking intentions [61]. As part of the annotation process, speech behaviors that did not involve speaking intentions were excluded.