CHARMING
Character Mining and Generation

The hero, the villain, the servant, the mentor, and many more ... movie and drama continue to rely on a repertoire of archetypical characters. But what makes a character? The proposed project CHARMinG will develop and apply AI methods from text and sentiment mining, natural language processing and machine learning to identify, from electronic sources of fictional dialogues (movie scripts, transcripts, drama texts), a set of indicators that convey the core of the relational/functional features and personality of characters, thereby leading to the generation of more colourful and engaging virtual characters.

The project endeavours to establish the field of character mining for both fictional and non-fictional text domains. Fictional texts are a useful starting point because we can benefit from the theoretical background on characters' design and rely on dialogue for their development. This research work will provide insights and methods for the design of artificial actors, assistive, educational, or entertaining virtual characters, and socially assistive robots. A central goal of the project is to make advances in the design of interesting virtual characters. These can be NPCs (non-player characters) for interactive stories, dramas, and games, but also assistive or educational agents, and their supporting cast. Through our research, which links textual surface features of a character to its underlying aspects in a systematic way, we endeavour at first to the modelling and generation of colourful, socially interrelated, and narratively supportive cast members that provide a social environment for the lead figures.

The project will also investigate the portability of the newly adapted and developed methods as well as their synergies to non-fictional, primarily dialogic, text genres, e.g. online social communities.

Research staff

• Robert Trappl
• Sabine Payr
• Marcin Skowron
• Martin Trapp
• Anna Dobrosovestnova

Sponsor