Scene Detection in Literary Fiction – Dennis Tenen – xpmethod.plaintext.in
Scene Detection in Literary Fiction – Dennis Tenen – xpmethod.plaintext.in
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scene-detection
On Github denten-talks / scene-detection
Scene Detection in Literary Fiction
Dennis Tenen
xpmethod.plaintext.in
Since our Last Time
Writing a book
Microscope!
Running a lab
Three research clusters:
- theory / method
- public discourse
- minimal computing
Two projects of interest to this group:
Emerging Consensus in Scientific Literature (w/ Dan Jurafsky, Dan MacFarland of Stanford, and Laura Kurgan of Spatial Information Lab)Scene Detection
Original Paper
Raymond WilliamsSuggested improvement: networks over time
Complexity! Lack of models for theoretical primitives.
- space
- time
- actors
- relations
Chunking. Preliminary observations:
- Typographical space (paragraph)
- Diegetic space (scene)
How do the two relate?
What is a scene?
Burke, Kenneth. A Grammar of Motives. University of California Press, 1969.
Rasheed, Z., and M. Shah. “Scene Detection in Hollywood Movies and TV Shows.” In 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings, 2:II – 343–48 vol.2, 2003.
Complications:
- actors can become scenes
- scenes can become actors
- scenes can involve mental states and ideologies
Proposed algorithm:
Separate actors from background through grammatical categories (object, subject, transitive verb, A blanks B)
Cluster scene particulates semantically to detect potential boundaries
Multiple passes to detect quality / movement (by analogy with video).
Ground truth, a stumbling block as always. To overcome: expert tagging, parallel copora. Any ideas?
We need better primitives to build more complex models!