Abstract

Oral story telling has become a lost art of family histories because social media and technology have taken over the personal interactions that once passed on the important stories and facts from generation to generation. This dissertation presents and evaluates a method of generating a narrative with input from the listener without actually forcing him or her to become an actual character in the narrative. This system is called CAMPFIRE Story Telling System (STS) and employs a contextual approach to story generation. This system uses the Cooperating Context Method (CCM) to generate and tell dynamic stories in real time and can be modified by the listener. CCM was created to overcome the weaknesses found in other contextual approaches during story generation while still meeting the design criteria of 1) being able to plan out a story; 2) being able to create a narrative that is entertaining to the listener; and 3) being able to modify the story that could incorporate the listener's request in the story. The CCM process begins by creating a list of tasks by analyzing the current situation. A list of contexts is narrowed down through a series of algorithms into two lists: high priority and low priority lists. These lists are analyzed and a set of context best suited to handle the tasks are selected. The CAMPFIRE STS was rigorously assessed for its functionality, novelty, and user acceptance as well as the time needed to modify the knowledge base. These evaluations showed that the CAMPFIRE STS has the ability to create novel stories using the same knowledge base. A group of 38 test subjects used and evaluated CAMPFIRE STS with respect to its use for children, story entertainment, story creativity and the system's ease of use answering a extensive survey of 54 questions. The survey showed that CAMPFIRE STS can create stories appropriate for bedtime stories with some minor modifications and that the generated stories are novel and entertaining stories, and that it was an easy system to use.

Graduation Date

2016

Semester

Summer

Advisor

Gonzalez, Avelino

Degree

Doctor of Philosophy (Ph.D.)

College

College of Engineering and Computer Science

Department

Electrical Engineering and Computer Engineering

Degree Program

Computer Engineering

Format

application/pdf

Identifier

CFE0006687

URL

http://purl.fcla.edu/fcla/etd/CFE0006687

Language

English

Release Date

February 2017

Length of Campus-only Access

None

Access Status

Doctoral Dissertation (Open Access)

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