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HOMER: A Creative Story Generation System Student: Dimitrios N. Konstantinou Supervisor: Prof. Paul Mc Kevitt School of Computing and Intelligent Systems.

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Presentation on theme: "HOMER: A Creative Story Generation System Student: Dimitrios N. Konstantinou Supervisor: Prof. Paul Mc Kevitt School of Computing and Intelligent Systems."— Presentation transcript:

1 HOMER: A Creative Story Generation System Student: Dimitrios N. Konstantinou Supervisor: Prof. Paul Mc Kevitt School of Computing and Intelligent Systems Faculty of Informatics University of Ulster, Magee

2 Objectives of HOMER To build a creative storytelling agent that generates:  style-constrained stories  stories with a point of view  natural language output  domain-independent stories

3 Literature Review Creativity Systems:  Copycat  Genesis  Letter Spirit  A Computational Model of Music  A Computational Model of Poetry

4 Schank’s Theory of CD, Scripts, and Stories  A Robotic Storyteller  An objection to Schank’s Theory  Scripts and Point of View  Story Grammars

5 Comparison with other storytelling systems

6 The Rationale for HOMER  Approximate the creative conceptual space in human narratives  Transform the conceptual space  Build domain-independence  Develop an extendable creative agent  Simulate author goals

7 Motivation  Create associative clusters of variables (“archetypical modes”)  Simulate high-level style decisions in story output  Introduce mid- / low-level style decisions  Simulate point of view  Create lexical entries and use transformational procedures

8 The Parser Input frame Language Understander Inference Mechanism Style Specifier Frame Constructor

9 The Story-outline Constructor Frame story-outline Mode-based Hierarchies Mode-based imagery

10 The Natural Language Generator Story narrative outline Narrative Reasoner Text Planner Narrative History Revisor Ontology Surface Realizer

11 Conclusion HOMER: a creative storytelling agent that:  takes as input a story fragment, style specifications and contextual clues  simulates authorial creative goals  generates narrative in the form of natural language output  approximates human language output

12 Software Tools Analysis Parsing:  Attribute Logic Engine (ALE 3.2)  Lexical Knowledge Base (LKB)  Rhetorical Structure Tool (RST) Natural Language Generation:  Upper Model from KPML  Systemic Unification Realization Grammar of English (SURGE)  I-SAURUS, lexicon for near-synonyms

13 Storytelling Systems  Structure-based Vs. Environment-based  Automatic Novel Writer (1973)  HOMER (2004)  AESOPWORLD(1996)  Larsen & Petersen (1999)  Story elements: story-line, plot, setting, style, point of view  Story Understanding  Creativity

14 Project plan

15 Architecture of HOMER Input output Parser Thematic Memory Story-Outline Constructor Natural Language Generator


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