Modeling Changing Perspectives — Reconceptualizing Sensorimotor Experiences: Papers from the 2014 AAAI Fall Symposium
A Computational Approach to Re-Interpretation:
Generation of Emphatic Poems Inspired by Internet Blogs
Joanna Misztal and Bipin Indurkhya
Faculty of Mathematics and Computer Science, Jagiellonian University, Krakow, Poland
Computer Science Department AGH University of Science and Technology, Krakow, Poland
Abstract
internal model of emotions with an individual optimism rate.
The system is empathic in that it extracts the emotional content of the text, which is then interpreted in its own way, so
the output state is not necessarily the same as the one expressed by the author of the text. The poems created by the
program focus on the inspiration phrase and contain words
that express those feelings. Hence the system does not just
repeat the essence of the input text but expresses (in the poems) its own interpretation and emotions evoked by reading
the text.
As stated in (Wiggins 2012) the inspiration underlying a
creative process is a spontaneous and unconscious phenomena that happens in the mind. Contrary to other problemsolving tasks, which must be performed in order, the act of
creation may be executed in parallel on various levels of
abstraction. This approach supports the Global Workspace
Theory (Baars 1997; 2003), in which the processes in mind
are performed by a group of independent specialized modules.
The architecture of our system is in accordance with the
assumptions of Baar’s theory. We use a blackboard model
consisting of a group of independent, specialized experts
(the knowledge sources). In our solution, each of the experts
represents some knowledge about the poetry-generation process. The experts cooperate using a common workspace - the
blackboard, where all the data is stored. Various modules
are triggered by the events on the blackboard. Each module,
when evoked, contributes according to its knowledge, creating partial solutions, which are posted on the blackboard.
These partial solutions, in turn, trigger other modules, and
so on.
This paper summarizes our previous work on the poetrygenerating system presented in (Misztal and Indurkhya
2014b) and (Misztal and Indurkhya 2014a) and presents a
new perspective on the generation process considering its
re-interpretation aspect. More details about the architecture
and implementation of the system can be found in the earlier
papers.
This paper is organised as follows. In the Background section we describe other systems that incorporate models of
emotions to interpret stimuli from the environment. We also
mention applications of the blackboard-related architectures
for the creative systems, and refer to the discussion about the
strong and weak computational creativity.
We present a system that produces emotionally rich poetry inspired by personalized and empathic interpretation of text, particularly Internet blogs. Our implemented system is based on the blackboard architecture,
and generates poetry from a theme that it considers the
most inspiring. It also incorporates a model of emotions
with an individual optimism rate that defines an affective state. The poems produced by the system contain
emotional expressions that describe these feelings. We
explain how the system re-conceptualizes the text by the
empathic interpretation of its content. We also present
how the blackboard architecture may support divergent
problem solving in the field of computational creativity.
We describe the system architecture and the generation
algorithm followed by some illustrative results. Finally,
we mention possible continuation of this work by incorporating other language generating systems as well
as human experts in the blackboard architecture.
Introduction
The act of creating art may be considered as a reconceptualization of an input stimuli (inspiration) into an
artistic artifact. A painter, when she or he creates a portrait,
does not necessarily replicate a precise image of the painted
object. The created work is the reflection of the author’s impressions and feelings inspired by some real phenomena.
Other artists work in a similar manner. They get some inspiration from the environment, interpret this information in
their own way, often dependent on their emotional state, and
create artifacts that express their point of view and feelings
evoked by the inspiring object or situation.
Our goal is to model this creative process of reconceptualization during the artists’ work. We describe here
a system that produces poems inspired by the input text.
For the experiment, we use fragments of Internet blog posts,
which usually carry some emotional content. Our system analyzes the text first, trying to find the most interesting term.
It rates phrases according to the number of diverse associations it can derive from each expression. Then we use the
computational empathy (Misztal and Indurkhya 2014b) to
define the emotional state. This state is calculated using an
c 2014, Association for the Advancement of Artificial
Copyright Intelligence (www.aaai.org). All rights reserved.
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content in poems has been used in MASTER (Kirke and Miranda 2013), where agents in various emotional states in a
society influence each other’s moods with their pieces of poetry. In (Colton, Goodwin, and Veale 2012), a corpus-based
poetry generator is presented that creates poems according
to day’s mood estimated from the news of the day. In (Davis
and Mohammad 2014) the system generates pieces of music from the text according to the emotions extracted from
reading the text.
In our system, the emotional state is acquired based on
the affective information extracted from the blog text, but it
is also dependent on the individual features of the system –
the model of emotions and its optimism rate that give the
system an individual personality. Hence the external factors
are used only as an inspiration for the theme and stimulus
for the affective state.
The Overview section explains the general idea of the system. The poetry-generation process in our approach is implemented on a blackboard model, which is described in the
System Architecture subsection. In this approach, the final
poetry is composed by a group of experts - each of whom
has some specific knowledge about the poetry-generation
process, and all of them share a global workspace called the
blackboard. The poetry-composition process is presented in
the Poetry Generation Algorithm section.
Some illustrative results are presented in the Examples
section and the Evaluation contains a summary of system’s
performance in the context of the proposed algorithm and
the final outputs evaluation.
In the Conclusions section we summarize our work and
propose possible continuation of this project by incorporating new experts representing other language generating systems as well as human users.
Blackboard architecture in computational
creativity systems
Background
In the blackboard model, the group of experts representing diverse knowledge sources cooperates using a common
workspace – the blackboard. It allows a range of different
”experts” represented as diverse computational models. This
architecture supports the Global Workspace Theory of mind
proposed in (Baars 1997; 2003), in which the consciousness
is compared to a theater where the actions are performed
by a large number of autonomous specialized modules (the
actors). Therefore the blackboard model has a potential to
be used for simulating cognitive processes, and it has already been applied in the field of computational creativity. For example, in the Slant system for story generation
(Montfort et al. 2013) the blackboard model combines separate subsystems dealing with plot, figuration, and the narrative discourse tasks in the generation problem. In (Wiggins
2012), the Global Workspace Theory has been proposed as
a model to simulate creative musics composition. Another
multi-agent approach to poetry generation is used in the later
version of WASP (Gervas 2010), where specialized families of experts cooperate during the poetry-generation process. Groups of agents work there as a cooperative society
of readers/critics/editors/writers. However, WASP does not
incorporate the blackboard model directly.
Strong and weak computational creativity
The possibility of creating a computer program which would
be capable of thinking and conscious understanding has
been argued during the debate over the weak vs. strong
AI. One of the claims against the strong AI has been illustrated in the Chinese Room Argument in (Searle 1980),
arguing that computations cannot lead to any conceptual
understanding even though they provide a meaningful output. An analogous discussion has grown around the weak
and strong computational creativity. In (al Rifaie and Bishop
2012) the Chinese Room experiment has been proposed in
relation to creativity. The authors claim that even if the system is capable of producing syntactically correct output, it
does not provide any understanding of the semantics.
We agree with the general claim that the generation of
emotionally-rich outputs inspired by an input implies neither understanding of the concept nor the ability to perceive
emotional stimulus by the program in a human way. However, as argued by (Gervas 2010), we claim that computational modesl of conscious process may significantly differ
from the original phenomenon because computers have distinct capabilities compared to humans. Incorporating cognitive models in the systems may lead to interesting solutions
by simulating creative processes in the brain, but still actions
performed by the computational units may be quite different
from the ones going on in the brain.
Overview
The system structure is based on the blackboard model. It
consists of a group of experts that represent diverse sources
of knowledge, the common blackboard workspace and the
control component that regulates the process. The modules
are described in the System architecture subsection.
At the beginning of the poetry-generation process, the input text is placed on the blackboard and the agents start to
work on it. Each agent has a special role and knowledge and
it waits until it finds something on the blackboard that it
can use for performing its task. When something interesting appears, the agent processes this information using its
individual knowledge and adds new partial solution to the
blackboard. The control module decides which agent’s contribution should be used for the final poem. The algorithm
Systems with empathy
As emotions have a strong impact on human-computer communication, there are many systems that imitate some empathic behaviors and adapt their mood to the environment.
Some of them extract and replicate the emotional content
of the input stimuli, while others use internal models of
emotions to define the mood. In (van der Heide and Trivino 2010), the authors propose a prototype system that defines its emotional state according to changing environmental conditions according to an internal emotional model. The
idea of using a model of emotions to generate emotional
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Model of emotions – A two-dimensional model, where
each emotional state is represented by coordinates in (valence, arousal) space. The emotions used in the model are
WordNet hyponyms of the word emotion in the WordNetAffect lexicon in the hierarchy of emotional categories.
The (valence, arousal) coordinates for emotional labels in
the model have been retrieved from the ANEW database
(Bradley and Lang 2010). The emotion model is described
in more details in (Misztal and Indurkhya 2014b).
is explained in more details in Poetry generation algorithm
subsection.
System architecture
The system architecture is presented in Figure 1. The main
modules of the system are described below.
Experts – Independent modules having access to the common blackboard. They are triggered by events on the blackboard – when they find something that they can use, they
add new information to the blackboard. Each module has
an individual knowledge and they all play diverse roles in
the system. Different experts work on the blackboard data at
different abstraction levels as shown in Table 1.
Control component – the unit responsible for setting the
initial constraints for the poem, setting the experts’ probabilities and selecting the expert whose contribution should be
used for the current line of poem. In the current version of
the system, it is possible to select the number of syllables in
lines, grammar form and rhyme pattern. The importance factors for the experts are chosen manually, and are used during
the generation process when an expert produces a number
of phrases proportional to its importance factor. The control
module also aims to maximize the diversity of the poem by
giving preference to the artifacts generated by those experts
that contributed less frequently before.
Figure 1: Blackboard architecture used in the system. The
text is input to the system. A group of specialized experts
processes it – some of them extract information and the
others generate new ideas inspired by information on the
blackboard. All partial solutions are added to the common
workspace until the poem is finished. The control component regulates the process by scheduling experts’ actions.
Blackboard is a common workspace, shared by experts,
with partial solutions and other information about the problem on various levels of abstraction. Detailed description
of the blackboard sections is presented in our former work
(Misztal and Indurkhya 2014b). Below we present a brief
description of the main sections of the blackboard.
Initial data – Information input manually at the beginning
of the process, containing the input text and the stylistic constraints such as number of lines, syllables, rhymes pattern as
well as grammatical requirements concerning tense and person.
Text analysis data– Information extracted from the text. It
consists of key phrases rated by the inspiration value (estimated as the number of associations that may be derived by
the experts), the topic of the poem selected as the most inspiring phrase and the emotional state defined according to
the sentiments in the text.
Pool of ideas – Words and partial solutions produced
by the experts. The expressions are derived from the topic
phrase and extended with the use of experts’ knowledge such
as lexical resources. The words in the pool are divided into
categories based on their grammatical form and meaning.
They may be used as an inspiration for other experts to produce new phrases. Solutions are rated by the selection experts according to the heuristics concerning the current constraints for poem lines.
Poem draft – Current version of the poem consisting of
lines. Each line is selected from among the phrase candidates by the evaluation experts.
Poetry generation algorithm
We present below the general algorithm for poetry generation. (For more details with an illustrative example see (Misztal and Indurkhya 2014b).)
1. Text and constraints are input by the user.
2. Steps 2-6 are repeated until the required number of lines
has been produced.
3. Text-analysis experts extract information from the input.
(a) Key phrases are extracted.
(b) Poem topic is selected.
(c) Emotional state is defined.
4. Word-generation experts add words associated with the
topic.
5. Poem-making experts construct expressions from words
on the blackboard.
6. Selection experts rate phrases according to constraints for
current line.
7. Control component makes the final selection of the poem
line considering the experts’ past frequencies.
Examples
We present below some example outputs of the system inspired by three input texts along with our remarks about the
interpretation.
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Abstraction level
Text analysis level
Words level
Collocations level
Phrases level experts
Control level experts
Expert
Keywords expert
Emotional
Keywords expert
WordNet expert
Emotional expert
WordNet expert
Collocation expert
Apostrophe expert
Comparison expert
Epithet expert
Metaphor expert
Oxymoron expert
Rhetorical expert
Emotional expert
Exclamation expert
Repetition expert
Syllables expert
Rhymes expert
Emotional expert
Random expert
Produced artifacts/examples
Key phrases
Emotional state
Words
Words - synonyms
Emotional words
Hypernyms, antonyms
Epithets, verbs, comparisons - words collocations
phrases: ”O life the musical being”
phrases:”As whole as a community‘’
Phrases:”Free modern theatre”
Phrases:”I am like the pleasant house”
Phrases:” Huge or little”
Phrases: “What is the royal house?”
Phrases: ”The tumult makes you anxious”
Phrases: “O theatre the free edifice! ”
Phrases - repetition
Selected phrases: number of syllables in lines
Selected phrases: rhyme measure in lines
Selected phrases: emotional state of the poem
Selected phrase: random selection
Table 1: Experts in the poetry generation process grouped by the abstraction level on which they work.
Compassionate poem about the way
money for Loma Linda University Childrens Hospital.
It was us with Katie Arminger and Jana Kramer was
supposed to headline, but she got sick. So that meant
we were the headliners! And that crowd could not have
been more gracious, rowdy, or amazing! We had the
BEST show. And we REALLY needed that. It was crazy
because we sold out of ALL of the merch we brought! Tshirts and Eps flew out the door! That was an amazing
feeling.
Inspired by the text:
Lately everyone has been wondering ”Is Jenelle and
Gary going to get back together?!”. NO! He is living
his life and I’m living mine. We are both happy with
our lives the way they are at the moment, I know for me
at least I’m EXTREMELY happy. Gary might of been
tweeting things because he might of been jealous in a
way that I was dating Courtland but he agrees to stop
today.
Topic: Huge theater, Emotion: anxiety,
Poem:
Topic: Whole way, Emotion: compassion,
Poem:
the grand manner born tenderly
oh way the cheerful property
she was like the general mode
guileless continuous manner
as whole as a distribution
she loved the mercifulness!
she was like the pastel-like style
great big theater
vast like a majority
why is the theater so entire?
she needs the insecurity
Remarks:
For this poem the rhyme constraints were selected.
Calm poem about New York
Remarks:
This poem has been generated from the phrase “whole
way” that was found to be the most inspiring as it provided
a wide range of word associations. Hence, the output poem
is lexically diversified. The emotional state is expressed by
the expression “mercifulness”.
Inspired by the text:
Anxious poem about the theater
Topic: New York, Emotion: Calmness
Poem:
Daniel and I felt so, so very fortunate to go here. The
timing could not have been more perfect for us as our
last few days in New York had been quite hectic. We had
been trying to wrap our heads around our lives without
anymore more fertility treatments.
Inspired by the text:
The show with KFrog out in Temecula California was
incredible. It was in a huge theater at the Pechanga
Casino. The show was for KFrog Cares which raises
she loved the peaceable new york
new like a revision
she was like the york
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Conclusions
she needed the easy house of york!
We proposed a system that is capable of re-conceptualizing
emotionally rich text by emphatic interpretation and composition of poems that express feelings evoked by reading the
text. The emotional state is defined by the model of emotions, and the mood is modulated by the optimism-rate factor
given to the character.
The blackboard architecture used in the system supports
flexibility and allows for a variety of solutions on various
abstraction levels leading to potentially creative solutions,
thereby simulating the inspiration and invention processes
in the mind. Analogous to the Baars’ Theater of Consciousness, the experts act on the scene of the blackboard, and their
cooperative play leads to the final solution.
The model also provides a way to combine diverse existing systems so that they may cooperate in the common
workspace. As the continuation of our work we would like
to incorporate in the system other poetry- and languagegenerating tools. We believe that the blackboard architecture
has a potential to contribute to the field of computational creativity by combining many of the existing approaches in this
domain.
Another interesting extension of this project would be creating an interactive blackboard system that would allow human experts to participate in the generation process and add
their phrases to the blackboard.The program could also visualize the generation process by displaying some of the data
appearing on the blackboard during the experts work. This
idea could provide a better understanding and interest in the
domain of creativity.
Remarks:
This example illustrates how the cooperation of experts
within a blackboard system may lead to creative solutions.
The well-known name “New York” has been broken up into
words and processed separately. The analysis on various abstraction levels provides an original and uncommon interpretation of the topic phrase.
Evaluation
As presented in the Examples section, the system is capable of re-conceptualizing input text and producing artifacts
that express its own interpretation of the analyzed data. As
shown in the last example, use of diverse experts within the
blackboard model supports creating novel and original associations at various levels of abstraction from well-known
expressions. Use of emotional words creates the impression
of intentionality and individual perception of the world. The
optimism rate affects the emotional perception and allows a
more individual interpretation. For instance, the same input
may cause the anxiety or anger emotional state depending
on the optimism rate.
However, the input text in the system is used rather as
an emotional and thematic inspiration than a concept to be
reinterpreted. As only one phrase from the text is selected
as the main topic for the poem, the overall sense and the
context of the input may be lost in the final artifact. This
aspect might be changed by taking under consideration more
ideas from the text and analyzing them in parallel to produce
a poem that combines more aspects of the inspiring stimulus.
In our recent work (Misztal and Indurkhya 2014b), we
presented an evaluation of our system considering both the
results, and the process by which they were generated according to some evaluation models for computational creativity systems and poetry generators. The blackboard system provided with a model of emotions generally was capable of producing outputs satisfying the triple constraints on
grammar, meaningfulness and poeticness provided by (Manurung, Ritchie, and Thompson 2012) as basic criteria for
evaluating poetry produced by a computer.
According to the FACE descriptive model (Colton, Charnley, and Pease 2011) our system performed creative acts of
form < Ag , C g , E g >. This means that the system (concept)
produces expressions using a fitness function evaluating the
(concept, expression) pairs with real-number values.
However, it was found that a weak point of the system,
according to both evaluation approaches, is the insufficient
definition of constraints for the outputs. In this work, we
managed to add a new constraint for the rhymes. As presented in Examples section, the system is capable of producing rhyming lines by selecting highest-rated phrases according to the constraints. However, this approach does not
yet provide satisfactory results as in many cases the phrasespace does not contain any rhyming candidates. This issue
needs to be further addressed and improved in the future
work.
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