# A Survey on Multi-User Conversational Interfaces
## 4 Capturing Multi-User Conversational Interfaces
### Application Domains and Examples
#### 4.1.2 Social Conversation  
[PERSON] et al. [15] present a spoken dialogue system prototype that can handle small talk between two agents having different characteristics and one human user. The subject of the small talk addresses the liking and disliking of different dishes, hence, making the agents' behaviour similar to human characteristics to study the interaction dynamics. During the dialogue, the agents can express opinions about specific dishes, e.g., \"I really like Miso Ramen.\", and engage in a conversation with users on their preferences. In doing so, the authors intended to create a more engaging conversation. [PERSON] et al. [16] extended the system to be able to change the topic of small talk to create more variation in the dialogues.  
Moreover, [PERSON] et al. [13] present a quiz-style multi-party dialogue system in which two artificial agents and two users engage in a conversation. One of the agents acted as the quiz-master, while the other agent acted as a peer which was engaging in finding the answer together with the human users. The goal of the quiz was to guess the name of a famous person. The quiz-master continuously provides hints until one of the human players or the peer agent finds the correct answers. The interface of the game was designed as a chat-like interface where users could type in their guesses.  
[PERSON] et al. [17] developed a sophisticated virtual agent framework that was able to handle social interactions between one user and multiple embodied agents. Here, the user was represented as an avatar in a 3D serious game environment. The game's goal was to successfully join a group of four agents (two males, two females) where the agents expressed various degrees of social behaviour (in-group vs. out-of-group attitudes). Even though the agents could express various interaction strategies, the conversational aspect was quite limited in the context of the author's application.  
In the realm of human-robot interaction, collaborative game-like scenarios have been explored, in which two users and a robot engage in discussions to find solutions [11]. The two visitors and a Furhat robot are given the task of sorting the cards according to specified criteria. For example, the task could be to sort a set of inventions in the order they were invented, or a set of animals based on how fast they can run. This is a collaborative game in which visitors have to discuss and find the solution together with a Furhat robot head.  
[PERSON] et al. [18] present a multi-party chatbot that can handle conversations based on logs from Ubuntu-related chat rooms, where multiple users discuss topics related to technical support with Ubuntu issues. Based on this Ubuntu-corpus, an annotated dataset intended for use in multi-user dialogue systems has been developed by [PERSON] et al. [19], wherethe authors included information about the addressee and response selection. For the realisation of the extraction model, the authors applied an end-to-end approach. Similarly, [PERSON] et al. [20] describe a multi-party chatbot that can take the role of a character of a specific TV show and communicate with multiple other agents representing one of the TV show's characters depending on its relation to the other dialogue participants.