Name
Title | ||
|---|---|---|
A Novel Approach to Interactive Dialogue Generation Based on Natural Language Creation with Context-Free Grammars and Sentiment Analysis |
Abstract | ||
|---|---|---|
The demand for high-quality video games is ever increasing and the ambition to tell truly interactive and dynamic stories is a significant factor contributing to this trend. This paper examines how generated narrative text is perceived by players in terms of meaningfulness, immersion, and flow and furthermore that the presented novel approach can be a valid method to implement computer-generated dialogues. For this approach, generative grammars are used to create written dialogue within a conversation for a learning application. With the support of sentiment analysis, the generated text is analysed with a focus on its semantics. Suitable text lines based on the current game state are provided by a dialogue system. Principles of gamification are used to create a learning application that renders such a generated dialogue scenario playable. To test this hypothesis, a user study examines the capabilities of the process by having players assess factors, which are imperative for a narrative game. The learning application shows strong potential in terms of text variation and dialogue that is easy to follow. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1109/ICALT49669.2020.00031 | 2020 IEEE 20th International Conference on Advanced Learning Technologies (ICALT) |
Keywords | DocType | ISSN |
natural language generation,dynamic storytelling,formal languages,sentiment analysis,gamification for learning | Conference | 2161-3761 |
ISBN | Citations | PageRank |
978-1-7281-6091-7 | 0 | 0.34 |
References | Authors | |
1 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Fabrizio Palmas | 1 | 2 | 1.39 |
| Jakob Raith | 2 | 0 | 0.34 |
| Gudrun Klinker | 3 | 1581 | 274.19 |