Creativity a pleasing field of bloom generating haiku poems
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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. Yoav Goldberg. ISI NL Seminar. Motivation. Why work on poetry generation?.

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Creativity a pleasing field of bloom generating haiku poems

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

Yoav Goldberg

ISI NL Seminar


Motivation

Motivation

Why work on poetry generation?


Motivation1

Motivation

  • It’s 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)


Motivation2

Motivation

  • It’s 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

Key Ideas - constraints

Form constraints aid creativity

  • help focus on content

  • force interesting solutions


Key ideas associativeness

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


Creativity a pleasing field of bloom generating haiku poems

People like to interpret / fill the gaps

 Poetry reading is also a creative process


Haiku

Haiku


Haiku1

Haiku

  • Form of poetry

  • Originated in Japan, 16th Century

  • Three lines of 5,7,5 phonetic units (mora)

  • Use present tense and use no judgmental words

  • Adopted in Western languages, 20th Century

  • Basho Haiku

  • 古池や蛙飛込む水の音

    • old pond . . .

    • a frog leaps in

    • water’s sound


Haiku2

Haiku


Amarican haiku

Amarican Haiku

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


Amarican haiku1

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."


Creativity a pleasing field of bloom generating haiku poems

old pond . . .

a frog leaps in

water’s sound

old pond

frog leaping

splash

pond

frog

plop!


Creativity a pleasing field of bloom generating haiku poems

picnic

in the sun-dappled courtyard

my freckled banana

my father and I

paint the barn

compare wars


Creativity a pleasing field of bloom generating haiku poems

fishing guides

boat in the background

a new trip

iced over pond

I skip a rock

the entire width

a holy cow

a carton of milk

seeking a church

blind snakeson the wet grasstombstoned terror

Holding up my

purring cat to the moon

I sighed

blossomless

but not unloved

the old magnolia

first date —

the little pile

of anchovies


Poetry generation

Poetry Generation


Creativity a pleasing field of bloom generating haiku poems

Bo

y

S

ul


Creativity a pleasing field of bloom generating haiku poems

Bo

y

S

ul

Structure


Creativity a pleasing field of bloom generating haiku poems

Bo

y

S

ul

Content

Structure


Creativity a pleasing field of bloom generating haiku poems

Bo

y

S

ul

Inspiring,

Interesting,

Intriguing,

Joyful,

3 lines,

Grammatical,

Haiku-like


Previous works

Previous works

  • Manurung [2003]

  • Manurung et al. [2000]

  • Gervas [2001]

  • Knight [2010]  future previous

    Emphasize on Structure, less on Content


Body structure

Body / Structure


Data driven

Data Driven

  • Haiku Corpus

    • ~3,500 Haiku in English

    • Various sources

      • amateurish sites

      • children’s 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

Pattern Extraction

Line 1 Patterns:

280 JJ NN276 NN NN...

Line 2 Patterns:

64 DT_the JJ NN

Line 3 Patterns:

….

NN IN_of NNPDT_a NN IN_ofNNS

NN NNNNS CC NNSIN_on DT_a NN NN

POS Tag

Count

Count

Pattern Transitions:

P(line2==DT_the NN | line1==JJ NN) = ...


Generation

Generation

Google 1T-Web / Proj Gutenberg

Line 1 Patterns:

280 JJ NN276 NN NN...

Line 2 Patterns:

64 DT_the JJ NN

Line 3 Patterns:

….

POS Tagged

Pattern Transitions:

P(line2==DT_the NN |

line1==JJ NN) = ...


Generation1

Generation

Google 1T-Web / Proj Gutenberg

Line 1 Patterns:

280 JJ NN276 NN NN...

Line 2 Patterns:

64 DT_the JJ NN

Line 3 Patterns:

….

POS Tagged

Pattern Transitions:

P(line2==DT_the NN |

line1==JJ NN) = ...

JJ NNSDT_a JJ NNIN_of NN


Generation2

Generation

Google 1T-Web / Proj Gutenberg

Line 1 Patterns:

280 JJ NN276 NN NN...

Line 2 Patterns:

64 DT_the JJ NN

Line 3 Patterns:

….

POS Tagged

match

Pattern Transitions:

P(line2==DT_the NN |

line1==JJ NN) = ...

JJ NNSDT_a JJ NNIN_of NN


Generation3

Generation

Google 1T-Web / Proj Gutenberg

Line 1 Patterns:

280 JJ NN276 NN NN...

Line 2 Patterns:

64 DT_the JJ NN

Line 3 Patterns:

….

POS Tagged

match

Pattern Transitions:

P(line2==DT_the NN |

line1==JJ NN) = ...

pouring catsa pilot careof fighter

JJ NNSDT_a JJ NNIN_of NN


Generation4

Generation

Google 1T-Web / Proj Gutenberg

Line 1 Patterns:

AA BB CC / 12

BB CC DD / 10

Line 2 Patterns:

CC DD EE / 20

Line 3 Patterns:

….

Grammatical output

Preserves Haiku “Texture”

POS Tagged

match

Pattern Transitions:

P(Line2=AA BB | Line1= XX YY)

pouring catsa pilot careof fighter

JJ NNSDT_a JJ NNIN_of NN


Generation5

Generation

Google 1T-Web / Proj Gutenberg

Line 1 Patterns:

AA BB CC / 12

BB CC DD / 10

Line 2 Patterns:

CC DD EE / 20

Line 3 Patterns:

….

Grammatical output

Preserves Haiku “Texture”

POS Tagged

Not a great story, though.

match

Pattern Transitions:

P(Line2=AA BB | Line1= XX YY)

pouring catsa pilot careof fighter

JJ NNSDT_a JJ NNIN_of NN


Creativity a pleasing field of bloom generating haiku poems

Soul?


Creativity a pleasing field of bloom generating haiku poems

Soul?

  • Requirements: good “story”

    • cohesive

    • surprising

    • provoke feelings/emotions

    • metaphorical

    • “Should leave the reader wondering…”

      … Creative!


Creativity a pleasing field of bloom generating haiku poems

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


Creativity a pleasing field of bloom generating haiku poems

Soul?

Is WordNet a good soul?

not really

it may give cohesiveness,

but bad stories


Butterfly spring flower

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


Word association norms wan

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).

    http://w3.usf.edu/FreeAssociation/

  • 5,019 cue words and 10,469 additional target that were collected with more than 6,000 participants since 1973.

    WAN – weighted directed graph, nodes are stemmed words.


Creativity a pleasing field of bloom generating haiku poems

water

spring

water

fall

fall

flower

butterfly

green

bloom


Why word associations

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

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

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

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 soul1

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

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 too1

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 too2

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

FREE:

the sample solution

free nude adult webcams

on a statutory holiday

ANIMAL:

animal nature

wild italian housewives

on a happy face


Education plays a role too3

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

FREE:

the sample solution

free nude adult webcams

on a statutory holiday

ANIMAL:

animal nature

wild italian housewives

on a happy face

CUTE:

cute college girls

young pussy cum

hardcore horse zoophilia

then we decided to switch to Gutenberg project


Evaluation

Evaluation?


Turing test

“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: AUTO set


Results sel set

Results: SEL set


Interesting observations

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

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

Thoughts on Turing tests

  • People are not very good at judging what a computer can or can’t 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

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

The Best of Gaiku

early dew

the water contains

teaspoons of honey

  • Best in SEL. Classified as human - 77.2%, average grade 3.09

  • Best in AUTO. Classified as human - 72.2%, average grade 2.75

cherry tree

poisonous flowers lie

blooming


Creativity a pleasing field of bloom generating haiku poems

fishing guides

boat in the background

a new trip

iced over pond

I skip a rock

the entire width

a holy cow

a carton of milk

seeking a church

blind snakeson the wet grasstombstoned terror

Holding up my

purring cat to the moon

I sighed

blossomless

but not unloved

the old magnolia

first date —

the little pile

of anchovies


Creativity a pleasing field of bloom generating haiku poems

fishing guides

boat in the background

a new trip

iced over pond

I skip a rock

the entire width

a holy cow

a carton of milk

seeking a church

blind snakeson the wet grasstombstoned terror

Holding up my

purring cat to the moon

I sighed

blossomless

but not unloved

the old magnolia

first date —

the little pile

of anchovies


Creativity a pleasing field of bloom generating haiku poems

fishing guides

boat in the background

a new trip

iced over pond

I skip a rock

the entire width

a holy cow

a carton of milk

seeking a church

blind snakeson the wet grasstombstoned terror

Holding up my

purring cat to the moon

I sighed

blossomless

but not unloved

the old magnolia

first date —

the little pile

of anchovies


Interesting stuff to be explored

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?


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