Spoken Conversational AI in Video Games: Emotional Dialogue Management Increases User Engagement
By Jamie Fraser, Ioannis V. Papaioannou, Oliver Lemon. 2018
52 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Developmental and Educational Psychology, Natural Language Processing
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Jason Aaron Edward Weston
- Eric Michael Smith
- Y-Lan Boureau
- Kurt Shuster
- Emily Dinan
- Arthur Szlam
- Jianfeng Gao
- Stephen Roller
In Developmental and Educational Psychology
- Jason Aaron Edward Weston
- Antoine Bordes
- Ivan Vulic
- D. Gunning
- Yuxing Peng
- Minghao Hu
- Xipeng Qiu
- Zhuosheng Zhang
In Natural Language Processing
- Jason Aaron Edward Weston
- Y-Lan Boureau
- Eric Michael Smith
- Kurt Shuster
- Emily Dinan
- Arthur Szlam
- Stephen Roller
- Da Ju
Citations in the corpus
- Open-Domain Conversational Agents: Current Progress, Open Problems, and Future Directions (2020, background): “…some level of empathy (Wentzel, 1997; Levinson, Gorawara-Bhat, and Lamb, 2000; Bickmore and Cassell, 2001; Kim, Kaplowitz, and Johnston, 2004; Fraser, Papaioan- nou, and Lemon, 2018), taken loosely as recognizing and acknowledging when the conversation partner displays some emotion, and…”
- Towards Empathetic Open-domain Conversation Models: A New Benchmark and Dataset (2018, background): “gaging in social talk, reacting to emotional cues and displaying a caring attitude have, in fact, been associated with better task outcomes in many domains (Wentzel, 1997; Levinson et al., 2000; Bickmore and Cassell, 2001; Kim et al., 2004; Fraser et al., 2018).”
- Learning to Speak and Act in a Fantasy Text Adventure Game (2019, neutral): “Other examples are instruction-following in the Neverwinter Nights game (Fleischman and Roy, 2005), studies of emotional response in adventure games (Fraser et al., 2018), dialogue about soccer videogames (Pasunuru and Bansal, 2018), placing blocks appropriately given a final plan (Wang et al.”
- ConveRT: Efficient and Accurate Conversational Representations from Transformers (2019, background): “…which closely follows a related line of work focused on modelling sentence pairs for short text retrieval (Kannan et al., 2016; Henderson et al., 2017), bilingual text mining and representation learning (Guo et al., 2018; Chidambaram et al., 2019), and question answering (Humeau et al., 2020).”
- A Repository of Conversational Datasets (2019, background): “They have found applications in entertainment (Fraser et al., 2018), language learning (Raux et al., 2003; Chen et al., 2017), and healthcare (Laranjo et al., 2018; Fadhil and Schiavo, 2019).”