1. An application of Markov models (sorta) Presented by Ehren Winterhof and Josh Whitver Ray Kurzweil’s Cybernetic Poet

2. Poetry Analysis Generates “Language Model” Poetry Generation Recursive Goal Driven Plagiarism Avoidance Algorithms Thematic Consistency Algorithms

3. Poetry Analysis Input – A collection of poems, usually by a single author Output – A “Markov model” of the author’s style and a poet personality file

4. Markov Models First used by Andrei Markov in 1913 in a letter- sequence analysis of the text of Eugene Onegin Markov Chains General Markov Models Hidden Markov Models

5. Markov Models Markov analysis takes a sequence of events and models the statistical likelihood that one event follows another. Useful for analyzing dependent random events (e.g., Weather, DNA Sequences, Speech Recognition, etc) Probability of transitioning to a given state depends only on current state, prior states are ignored. (the Markov Property)

6. Markov Model vs. Hidden Markov Model Regular Markov models output a sequence of states Each state has a unique name, so the output uniquely determines the path through the model Hidden Markov Models can have the same output appear in more than one state Each state has a probability distribution of possible outputs

7. Hidden Markov Models Describes a probability distribution over a potentially infinite number of sequences Probability distribution must sum to one, so “scores” that an HMM assigns to sequences are constrained

8. t 1,1 t 1,2 t 2,2 t 2,end 12end p 1 (a) p 1 (b) p 2 (a) p 2 (b) 112 end aba Hidden state sequence, π Observed symbol sequence, x t 1,1 t 1,2 t 2,end p 1 (a) p 1 (b) p 2 (a) P( x,π | HMM)

9. How a purely Markovian process might generate poetry Poetry analyzer reads sample poetry to determine the likelihood that one word follows another From the start state take a random path to a final state, picking up a word at each node visited. That’s it

10. How RKCP works (maybe) Not “true” Markov Models “Goal-driven” traversal Separate algorithms influence form and theme of poem, while avoiding plagiarism

11. Poet Personality Defines how a poem should be generated from the Poet Style model. Parameters How tightly to comply with the Poet Personality model Poem type : Free Verse, Haiku, Cinquain, Structured, Thin, etc. Theme Usage

12. Maintaining Thematic Consistency Determined by Poet Personality Keyword directs “train of thought” Weighted Random Selection Variable “Thematic Intensity”

13. Poetry-Specific Turing Test Featuring Ray Kurzweil’s Cybernetic Poet

14. Sample 1 is a steady burning the road the battle's fury- clouds and ash and waning sending out young people,

15. Sample 2 Wipe your hand across your mouth, and laugh; The worlds revolve like ancient women Gathering fuel in vacant lots.

16. Sample 3 0 thou, Who moved among some fierce Maenad, even among noise and blue Between the bones sang, scattered and the silent seas.

17. Sample 4 Oh! did appear A half-formed tear, a Tear. By the man of the heart.

18. Sample 5 By action or by suffering, and whose hour Was drained to its last sand in weal or woe, So that the trunk survived both fruit or flower;-

19. Answers 1.RKCP after reading the poetry of William Carlos Williams 2.T. S. Eliot 3.RKCP after reading T. S. Eliot and Percy Bysshe Shelly 4.RKCP after reading Lord Byron 5.Percy Bysshe Shelley

20. Other AI Poetry Projects Pujangga Ruli Manurung (University of Indonesia) Genetic Algorithm Bahasa Poetry CreatOR 2 Jeff Lewis and Erik Sincoff (Stanford) Mad Libs Racter William Chamberlain (INRACK Corp) First AI to “write” a book