An application of Markov models (sorta) Presented by Ehren Winterhof and Josh Whitver

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

2. Ray Kurzweil’s Cybernetic Poet • 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. t1,1 t2,2 t1,2 t2,end 1 2 end p1(a) p1(b) p2(a) p2(b) end 1 1 2 Hidden state sequence, π a b a Observed symbol sequence, x P(x,π | HMM) t1,1 t1,2 t2,end p1(a) p1(b) p2(a)

8. 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

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

10. 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

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

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

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

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

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

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

17. 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;-

18. Answers • RKCP after reading the poetry of William Carlos Williams • T. S. Eliot • RKCP after reading T. S. Eliot and Percy Bysshe Shelly • RKCP after reading Lord Byron • Percy Bysshe Shelley

19. 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