creativity / a pleasing field / of bloom: Generating Haiku Poems Read all about it: Gaiku: Generating Haiku with Word Association Norms Yael Netzer, David Gabay, Yoav Goldberg and Michael Elhadad ISI NL Seminar Yoav Goldberg

Motivation Why work on poetry generation?

Motivation Its cool Seem like a fun thing to do We like doing fun stuff and being cool (also, nice that wife is actually interested in what you do for a couple of weeks)

Motivation Its cool Seem like a fun thing to do We like doing fun stuff and being cool (also, nice that wife is actually interested in what you do for a couple of weeks) You can have fun and do cool stuff too! give computational creativity a shot

Key Ideas - constraints Form constraints aid creativity help focus on content force interesting solutions

Key Ideas - associativeness Associations are central to human thinking Associations are at the core of creativity Associations are key to poetry perception Many associative layers can be active simultaneously and contribute to meaning

People like to interpret / fill the gaps Poetry reading is also a creative process

Haiku

Form of poetry Originated in Japan, 16 th Century Three lines of 5,7,5 phonetic units (mora) Use present tense and use no judgmental words Adopted in Western languages, 20 th Century Basho Haiku old pond... a frog leaps in waters sound

Haiku

Amarican Haiku Mainly I've been back to my books and writings and being nice and quiet and lazy.

Amarican Haiku The American Haiku is not exactly the Japanese Haiku. The Japanese Haiku is strictly disciplined to seventeen syllables but since the language structure is different I don't think American Haikus (short three-line poems intended to be completely packed with Void of Whole) should worry about syllables because American speech is something again...bursting to pop. Above all, a Haiku must be very simple and free of all poetic trickery and make a little picture and yet be as airy and graceful as a Vivaldi Pastorella."

old pond... a frog leaps in waters sound pond frog plop! old pond frog leaping splash

picnic in the sun-dappled courtyard my freckled banana my father and I paint the barn compare wars

iced over pond I skip a rock the entire width blossomless but not unloved the old magnolia fishing guides boat in the background a new trip a holy cow a carton of milk seeking a church blind snakes on the wet grass tombstoned terror first date the little pile of anchovies Holding up my purring cat to the moon I sighed

Poetry Generation

Bo y Sul

Bo y Sul Structure

Bo y Sul Structure Content

Bo y Sul 3 lines, Grammatical, Haiku-like Inspiring, Interesting, Intriguing, Joyful, …

Previous works -Manurung [2003] -Manurung et al. [2000] -Gervas [2001] -Knight [2010] future previous Emphasize on Structure, less on Content

Body / Structure

Data Driven Haiku Corpus –~3,500 Haiku in English –Various sources amateurish sites childrens writings translations of classic Japanese Haiku of Bashu and others official sites of Haiku Associations (e.g., Haiku Path - Haiku Society of America).

Pattern Extraction POS Tag Count Line 1 Patterns: 280 JJ NN 276 NN NN... Line 2 Patterns: 64 DT_the JJ NN … Line 3 Patterns: …. Count Pattern Transitions: P(line2==DT_the NN | line1==JJ NN) =... … NN IN_of NNP DT_a NN IN_of NNS NN NN NNS CC NNS IN_on DT_a NN NN …

Generation Line 1 Patterns: 280 JJ NN 276 NN NN... Line 2 Patterns: 64 DT_the JJ NN … Line 3 Patterns: …. Pattern Transitions: P(line2==DT_the NN | line1==JJ NN) =... … Google 1T-Web / Proj Gutenberg POS Tagged

Generation Google 1T-Web / Proj Gutenberg POS Tagged JJ NNS DT_a JJ NN IN_of NN Line 1 Patterns: 280 JJ NN 276 NN NN... Line 2 Patterns: 64 DT_the JJ NN … Line 3 Patterns: …. Pattern Transitions: P(line2==DT_the NN | line1==JJ NN) =... …

Generation Google 1T-Web / Proj Gutenberg POS Tagged match JJ NNS DT_a JJ NN IN_of NN Line 1 Patterns: 280 JJ NN 276 NN NN... Line 2 Patterns: 64 DT_the JJ NN … Line 3 Patterns: …. Pattern Transitions: P(line2==DT_the NN | line1==JJ NN) =... …

Generation Google 1T-Web / Proj Gutenberg POS Tagged match JJ NNS DT_a JJ NN IN_of NN pouring cats a pilot care of fighter Line 1 Patterns: 280 JJ NN 276 NN NN... Line 2 Patterns: 64 DT_the JJ NN … Line 3 Patterns: …. Pattern Transitions: P(line2==DT_the NN | line1==JJ NN) =... …

Generation Line 1 Patterns: AA BB CC / 12 BB CC DD / 10 … Line 2 Patterns: CC DD EE / 20 … Line 3 Patterns: …. Pattern Transitions: P(Line2=AA BB | Line1= XX YY) … Google 1T-Web / Proj Gutenberg POS Tagged match Grammatical output Preserves Haiku Texture JJ NNS DT_a JJ NN IN_of NN pouring cats a pilot care of fighter

Generation Line 1 Patterns: AA BB CC / 12 BB CC DD / 10 … Line 2 Patterns: CC DD EE / 20 … Line 3 Patterns: …. Pattern Transitions: P(Line2=AA BB | Line1= XX YY) … Google 1T-Web / Proj Gutenberg POS Tagged match Grammatical output Preserves Haiku Texture JJ NNS DT_a JJ NN IN_of NN pouring cats a pilot care of fighter Not a great story, though.

Soul?

Requirements: good story –cohesive –surprising –provoke feelings/emotions –metaphorical –Should leave the reader wondering… … Creative!

Soul? An idea: capture story seed as sequence of concepts butterfly, spring, flower thief, steal, jail mosquito, blood, vampire but not any seed will do cat, feline, claw too cohesive computer, coat, queen too divergent

Soul? Is WordNet a good soul? not really it may give cohesiveness, but bad stories

Butterfly Spring Flower The connection between these words is reconstructable by human It is not available in WordNet Where can we find such relations?

Word Association Norms

Word Association Norms (WAN) Collection of cue words a set of free associations (targets) with quantitative and statistical measures. (mouse CAT 0.5, RAT 0.08, CHEESE 0.07, HOLE 0.05…) Given a cue - collect immediate responses of first word that comes to mind. Largest WAN we know for English is the University of South Florida Free Association Norms (Nelson et al., 1998). 5,019 cue words and 10,469 additional target that were collected with more than 6,000 participants since WAN – weighted directed graph, nodes are stemmed words.

water flower butterfly spring fall green water bloom

Why Word Associations Added value of WAN: an insight on language, not found in WordNet or are hard to acquire from corpora [Sinopalnikova & Smrz 2004] Associative thinking takes part in the process of writing and reading poetry Haiku, because so short - relies on lexical associations for concept progression Hypothesis: word-associations are good catalyzers for creativity, can be used as a building block in the creative process of Haiku generation.

Filling body with soul: Theme Selection Generating the seed of the story: –Start with a word random walk on a word graph Many possible variants. We currently use: start with the node of the seed word do several short random walks keep resulting word set

Filling body with soul Input: seed word -generate structural skeleton -perform several short random walks on Assoc. graph, creating an association set -choose first line containing seed word -choose other lines containing a word from the set This is adequate, but relations might be too straightforward

Searching for a better soul Generate several poems for the pattern, then select the best one (people do that too: try out various ideas, write, rewrite, throw away, chose best one)

Searching for a better soul Generate several poems for the pattern, then select the best one (people do that too: try out various ideas, write, rewrite, throw away, chose best one) We rank haikus based on associativity measure This ranking catches further residual relations

Education plays a role too.. At first we used Google web n-grams SILVER : golden age of animation saves a lot of money with fish

Education plays a role too.. At first we used Google web n-grams SILVER : golden age of animation saves a lot of money with fish ANIMAL : animal nature wild italian housewives on a happy face

Education plays a role too.. At first we used Google web n-grams SILVER : golden age of animation saves a lot of money with fish ANIMAL : animal nature wild italian housewives on a happy face FREE : the sample solution free nude adult webcams on a statutory holiday

Education plays a role too.. At first we used Google web n-grams then we decided to switch to Gutenberg project SILVER : golden age of animation saves a lot of money with fish ANIMAL : animal nature wild italian housewives on a happy face FREE : the sample solution free nude adult webcams on a statutory holiday CUTE : cute college girls young pussy cum hardcore horse zoophilia

Evaluation?

Turing Test Was this Haiku written by human or computer? How would you rate it between 1 to 5? Settings: –AUTO: 15 Haiku created by Gaiku without any manual selection, 10 random human Haiku (same seed words) –SEL: 17 Haiku created by Gaiku, selected manually out of several runs, 9 award winning human Haiku 52 subjects

Results: AUTO set

Results: SEL set

Interesting observations Every subject was wrong at least 3 times –at least once in each direction CS students better at recognizing computer poems than Foreign Literature Students Foreign Literature students assign higher scores in general

Some subjects comments: On computer generated: this is too stupid to be written by a computer On human generated: this metaphor is too trivial to be written by a human

Thoughts on Turing tests People are not very good at judging what a computer can or cant do Who is under test in a Turing test? –The computer program? –The human haiku writers? –The human participating in the test?

Regardless of evaluation limitations I feel Gaiku is indeed a reasonable Haiku poet It is certainly better than me at writing Haiku poems I find myself constantly amazed by some of its outputs I find many of them to be intriguing / thought-provoking / amusing / fascinating. I can definitely recognize Gaiku outputs from Human poems. But maybe it just means it has a distinct style?

The Best of Gaiku Best in SEL. Classified as human %, average grade 3.09 Best in AUTO. Classified as human %, average grade 2.75 early dew the water contains teaspoons of honey cherry tree poisonous flowers lie blooming

iced over pond I skip a rock the entire width blossomless but not unloved the old magnolia fishing guides boat in the background a new trip a holy cow a carton of milk seeking a church blind snakes on the wet grass tombstoned terror first date the little pile of anchovies Holding up my purring cat to the moon I sighed

iced over pond I skip a rock the entire width blossomless but not unloved the old magnolia fishing guides boat in the background a new trip a holy cow a carton of milk seeking a church blind snakes on the wet grass tombstoned terror first date the little pile of anchovies Holding up my purring cat to the moon I sighed

iced over pond I skip a rock the entire width blossomless but not unloved the old magnolia fishing guides boat in the background a new trip a holy cow a carton of milk seeking a church blind snakes on the wet grass tombstoned terror first date the little pile of anchovies Holding up my purring cat to the moon I sighed

Interesting stuff to be explored Better modeling of association progression –Can we model Surprise? Suspense? –Higher-order associations Can we create association priming? Can we create association-garden-pathing? There is more to haikus than associations Can we generate based on a theme, not just a seed word?