## 2 Literature Review  
Human-cobot communication plays an important role in task allocation and the safety of collaborative assembly systems [8; 9]. [PERSON] et al. [10] also examined the static vs. dynamic task allocation preferences of human workers and found that they preferred adaptive task sharing (ATS) to static predetermined task allocation and reported increased satisfaction with dynamic allocation. Workers are more likely to assign manual tasks to cobots, while preferring to handle cognitive tasks themselves [10]. These dynamic characteristics of collaboration require good communication between humans and cobots. Cobot-human communications could take one of the following forms (as summarized in Table 1):  
* _Text communications_: The human worker uses text for programming the cobot, and to send it commands and information [11]. The cobot may also use text to communicate messages, explanations, cautionary warnings, and other information types [12; 13]. * _Visual communications_: Graphical displays, AR, and vision systems are key components of visual interfaces that enable workers to comprehend and interpret information from cobots efficiently [14; 15]. Graphical displays can provide real-time feedback on cobot actions, task progress, and system status, enhancing transparency and situational awareness [16]. AR overlays digital information onto the physical workspace, offering intuitive guidance for tasks and aiding in error prevention [17]. Vision systems, equipped with cameras and sensors, enable cobots to recognize and respond to human gestures, further fostering natural and fluid interaction [18]. * _Auditory communications_: Human-cobot vocal communication has been a topic of intensive research in recent years [19]. Auditory cues are valuable in environments where visual attention may be divided or compromised [20]. Sound alerts, spoken instructions, and auditory feedback mechanisms contribute to effective communication between human workers and cobots [21]. For instance, audible signals can indicate the initiation or completion of a task, providing workers with real-time information without requiring constant visual focus [22]. Speech recognition technology enables cobots to understand verbal commands, fostering a more intuitive and dynamic interaction [23]. The thoughtful use of auditory interfaces between humans and cobots helps create a collaborative environment where information is conveyed promptly, enhancing overall responsiveness and coordination [24]. Several recent papers have proposed novel interfaces and platforms to facilitate this type of interaction. [PERSON] and [PERSON] [25] introduced a framework that detects and recognizes speech messages, converting them into spoken commands for operating system instructions. [PERSON], [PERSON], and [PERSON] [26] proposed a network-independent verbal communication platform for multi-robot systems, which can function in environments lacking network infrastructures. [PERSON] et al. [27] highlighted the importance of conversation as a natural method of communication between humans and robots, promoting inclusivity in human-robot interaction. [PERSON] et al. [28] conducted a user study to understand the impact of robot attributes on team dynamics and collaboration performance, finding that vocalizing robot intentions can decrease team performance and perceived safety. [PERSON] and [PERSON] [29] found that voice-activated robot programming is more efficient than typing and other programming techniques. These papers collectively contribute to the development of human-robot vocal communication systems and highlight the challenges and opportunities in this field. * _Tactile communications_: The incorporation of tactile feedback mechanisms enhances the haptic dimension of human-cobot collaboration [30]. Tactile interfaces, such as force sensors and haptic feedback devices, enable cobots to perceive and respond to variations in physical interactions [31].