Science of Story
Department of Music
Abstract: Story is a delicate balance. Can a computer appreciate a good story? Probably not, at least not yet today. But it can help weigh the options and make cold-blooded calculations of how well story elements combine according to some commonly accepted script-writing formulas. In the talk I will describe an ongoing research on using NLP to track the structure of narrative in film scripts by embedding scenes in a semantic space and tracing their evolution over time. The method allows matching theoretical elements of story structure, such as theme, turning points, B-story, climax and resolution, and many other elements outlined in so called "beat-sheet" formulas to actual changes in word statistics over the duration of a film script. This automated analysis can be compared to previous research on green lighting movie scripts that uses human evaluations as predictors for commercial success of movies. Some speculations on universality of story structure in relation to human perception of epic / myth and musical form will be discussed.
Shlomo Dubnov is a Professor in music technology at UCSD. He received his PhD in Computer Science from Hebrew University and was a researcher in IRCAM, Paris and faculty in Communication Systems Engineering in Ben-Gurion University, Israel. Among his main contributions are new methods for statistical audio analysis/synthesis, modeling of emotions and aesthetics, and machine learning systems for musical improvisation. He co-edited a book “The Structure of Style: algorithmic approaches to understanding manner and meaning” and served as a secretary of IEEE Technical Committee on Computer Generated Music. Currently he serves as a co-lead editor of ACM Computers in Entertainment and directs Qualcomm Institute's Center for Research on Entertainment and Learning (CREL).
Posted by Charles Elkan