Abstract
In this paper, we describe Oupoco (l’Ouvroir de Poésie Combinatoire), a system producing new sonnets by
recombining lines of poetry from existing sonnets, following an idea that Queneau described in his
book Cent Mille Milliards de poèmes (A Hundred Thousand Billion
Poems, 1961). We first give the rationale of the project and review past experiments in poetry generation
using combinatorial methods. We then demonstrate different outputs of our implementation (a Web site, a Twitter bot
and a specifically developed device, called the Boîte à poésie) based on
a corpus of 19th century French poetry. We describe how this project was an opportunity to work with artists and
reach a new audience through the Boîte à poésie, and also through a
video clip that frequently served as an introduction to the project. Our goal is to revive people’s interest in
poetry by giving access to automatically produced sonnets through original and entertaining channels and
devices.
1 Introduction: Combinatorial Literature, from Queneau to Oupoco
The Oupoco project is a project exploring combinatorial methods to produce poetry by recombining existing lines of
poetry. The starting point of the project was the book by Raymond Queneau,
Cent
Mille Milliards de poèmes (
A Hundred Thousand Billion Poems, in English)
[
Queneau 1961].
This book is composed of ten sonnets, each line being printed on a separate strip of paper (
Figure 1), allowing the reader, by freely combining the different lines, to potentially
produce and read a hundred thousand billion different sonnets. This combinatorial approach (the main characteristic
of the book) encourages the reader to play with the meanings of the lines, with the various language registers, or
simply to have fun with the book. It is this stimulating relationship between poetry and constraints that we wanted
to reproduce and that was the mainspring of our project.
Queneau’s book seems an ideal candidate to be transposed to a computer, since a machine can very
easily combine lines and produce a comprehensive list of all the possible poems. However, Queneau’s
work is still under copyright, which should normally prevent one from putting the sonnets contained in his book
online, although numerous implementations can in fact be found on the Internet. Nevertheless, this is one of the
reasons why, instead of working on Queneau’s poems, we decided to focus on freely available ones,
which also helped develop more original and challenging research. Hence, an important part of the project consisted
in constituting a collection of 19th century French sonnets.
Beyond the availability of relevant collections of poetry, which facilitated the creation of our corpus,
19th century poetry also appeared as a fertile ground to reflect upon the sonnet and to work and play with various
constraints. This means that the original poems first have to be analyzed so as to determine the rhyme, as well as
other features (line length, topic of the sonnet, etc.). Our project thus deals with analysis, as much as with the
generation of poetry. We will see that the project gave birth to various outputs, including artistic ones. Finally,
we made several public demos, showing that such a project can have an impact on the general public as well as on
children in school, in a learning perspective.
The structure of the paper is as follows. We will first examine some past work and give our motivations for this
project (
Section 2). We then describe the corpus (
Section
3), the approach for rhyme analysis (
Section 4), and the constraints on the
generation process (
Section 5). We conclude the technical part of the paper with an
evaluation of the sonnets thus generated (
Section 6). We then describe our
collaboration with artists, to produce the
Boîte à Poésie, and the
Oupoco video clip (
Section 7). This led to different demonstrations and some
outreach initiatives with the public (
Section 8). We conclude with a discussion on
computers and creativity (
Section 9).
2 Computational Combinatorial Poetry, from Queneau to Oupoco
In this section, we examine some past experiments to generate poetry with computers in the context of the
Oulipo
[1]. We then describe the
rationale behind our project, inspired by Queneau but also largely departing from
Oulipo’s original ideas.
2.1 Transposing Queneau’s Book to a Computer
As mentioned in the introduction, there have been various attempts to transpose Queneau’s book to a
computer. In fact, in 1961, immediately after the publication of the book, a first attempt was made by Dimitri
Starynkevitch, a French computer scientist, working on a computer of the time (a CAB 500, to be precise,
according to Bens (
2005); see
Figure 2 and [
Starynkevitch 1990]. Baillehache (
2021) reports
Oulipo’s answer to Starynkevitch’s program: “We wished that M.
Starynkevitch would explain the method used; we hoped that the choice of the verses was not left to
randomness” [
Bens 2005, 79]. As Baillehache explains, this answer “reflects mistrust against randomness”; moreover, it shows
Oulipians’ lack of interest, in 1961, in the process that would make it possible to generate poetry indefinitely
and automatically, which may seem surprising at first glance.
It is indeed not entirely clear why Queneau and Oulipo reacted in this way.
Baillehache (
2021), after Bloomfield and Campaignolle (
2016), attributed it to Oulipo's aversion to randomness, seen
as opposite to the idea of constraints that the group explored intensively in its literature.
While this is possible, we also think that the main goal of Queneau was not just to produce an
infinite number of poems generated randomly. The book, with its strips of paper, is in fact more than a book, it
is also a piece of art and an object conceived as a device to be manipulated by people. The whole idea is to
assemble lines of verse, look at the result, try other possibilities and produce silly, funny, or just unexpected
poems. The transposition to a computer in 1961, and most of the implementations one can find online nowadays, do
not allow this: they produce poems, one at a time, randomly, without any possible interaction with the end-user
or the reader.
Since the advent of the Web in the 1990s, many other implementations (transposing Queneau’s book
and ideas online) have been proposed over the years. But there were many attempts even before that.
Leonardo/Olats and Philippe Bootz (
2006) give an interesting survey of
what they call
combinatorial generative literature (
littérature generative
combinatoire, in French). The authors report that Paul Braffort, from Oulipo, developed a
computer version of the book in 1975, for an exhibition (Europalia) in Brussels. Tibor Papp, another enthusiast
of computer literature, who worked with Bootz in the 1980s, also developed in 1988 an electronic version of the
book (
Figure 3). Last but not least, a version was developed by Antoine Denize and
Bernard Magné for the CD-ROM
Machines à écrire, in which the text is
enhanced with graphic effects that were not part of Queneau’s original project (
Figure 4). This CD-Rom, published by one of the most prestigious publishers in France
(who is also the publisher of Queneau’s work), had a wider audience that the previous programs,
which reached only a limited readership.
In the 1990s, a natural move consisted in implementing versions on the Web. A memorable event occurred in 1997,
when a French computer science student was summoned to court by a descendant of Queneau, because he
had put online a version replicating Queneau’s book (thus breaching the copyright). The event
attracted some attention, at least in France, as one of the first cases sending someone to court for a violation
of literary property on the Internet
[2].
In the end, the court sentence was mild (as the program had already been removed from the Internet). Since then,
the magnitude of the problem of online piracy (the practice of downloading and distributing copyrighted works
digitally without permission) has downgraded this episode to a mere incident. To the best of our knowledge,
nobody else since then has encountered problems with online versions of Queneau’s book, even if they
infringe copyright laws. Their readership is in any case extremely limited.
While Oulipo members initially showed some interest in computers, this did not last for very long,
as we have seen above. To revive this topic, a specific group, called Alamo (
Atelier de Littérature Assistée par la Mathématique et les Ordinateurs), comprising members of the
Oulipo but also (and mostly) academics and computer scientists interested in the connections
between literature and computers, was created in 1982. While this group developed interesting ideas and pieces of
software, it remained independent of the Oulipo, and in turn the Oulipo did not show a
great interest in the activities of this group. Moreover, the rapid obsolescence of computer programs made their
production hard to maintain and showcase. More recently, Natalie Berkman (
2017,
2022) tried to reproduce some of the early experiments of the
Oulipo with computers and, more specifically, she tried to understand why the Oulipo
quickly abandoned the idea of exploring this topic. Developing a program on a computer in the 1960s was complex
(it involved preparing large sets of punch cards for example; it is no coincidence that the Alamo was created in
1982, with the advent of the personal computer). Moreover, it was not really possible at that time to represent
the whole complexity of a language on a computer, and computers did not offer any real advantages compared to
mathematical or formal models described on paper. As a result, in Berkman’s words (
2022), the Oulipo’s members showed “a clear
preference for abstract mathematical thought — patterns and structure — rather than the procedural tendencies
of applied mathematics”. But let’s now come back to our own experiment.
2.2 Beyond Cent Mille Milliards de poèmes, our own
experiment
In an interview with Georges Charbonnier (
1962), Queneau
explained that
potential literature (
la littérature potentielle) is
“the search for forms, [...] for new structures which can then be used by writers in
whatever way they like” [
Charbonnier 1962, 140]
[3]. Our own experiment here aims at reviving not only an interest in poetry but also aims at
exploring new ways of writing, at a time when text is everywhere around us. For this, we also took inspiration
from the notion of
uncreative writing, as defined by Kenneth Goldsmith [
Goldsmith 2011]
[
Goldsmith 2019].
Uncreative Writing challenges conventional notions of creativity and authorship in
the realm of literature. Goldsmith's approach advocates for a departure from the traditional, romanticized image
of the writer as a solitary genius crafting original, imaginative works. Instead, he promotes the idea that
creativity can also be found in the act of appropriation and remixing, where writers repurpose existing texts,
often without significant alteration, to create something new and thought-provoking. This notion blurs the lines
between authorship, plagiarism, and creativity, emphasizing the power of the remix culture and the vast reservoir
of existing texts as a source of inspiration. Uncreative Writing invites us to reconsider the boundaries of
creativity in the digital age, where information is abundant and easily accessible, fostering a literary
landscape that celebrates the art of recontextualization and the collaborative nature of language itself.
Another important point, especially if we place ourselves in the continuation of the Oulipo
tradition, is the role of randomness (or chance) in generating texts. In Jacques Bens' account of the early
Oulipo meetings, there is extensive discussion on this topic, and Queneau believed
that writers should always be conscious of the constraints they are using and leave nothing to chance. In this
sense, Oulipo wanted to affirm its departure from other literary movements, first and foremost
surrealism. Our project aligns with this idea, in a way: we focus on sonnets, and the goal is to respect as much
as possible the constraints of this specific poetic form. However, the notion of chance should not be confused
with the notion of
potential literature (
la
littérature potentielle): there is still an infinity of possible (potential) poems, even when taking
into account all the constraints that apply [
Fournel 1972]
[
Oulipo 1973]
[
Oulipo 1981]
[
Oulipo 2002].
Producing computational combinatorial poetry inspired by Raymond Queneau's One
Hundred Thousand Billion Poems using publicly available poems opens up a large number of possibilities.
By dissecting and reassembling publicly accessible verses through code, we can explore an infinity of poetic
possibilities, taking into account constraints. Each line and word are placed in a new context, forging
connections and juxtapositions that transcend the individual poems' original contexts. Through this experiment,
we pay homage to Queneau's legacy while showcasing the potential of technology to popularize poetry,
enabling anyone to explore poetry and computational creativity.
3 The Corpus
The first part of this research consisted in gathering a corpus of French sonnets from the 19th and early 20th
century. Although there are famous sonnets from the 16th and 17th century in French, we choose to focus mainly on
the 19th century in order to build a more homogeneous corpus, both from a thematic and linguistic point of view
(19th century French is more normalized than the language a few centuries before). We first used resources that
were freely available on the Web, especially from the Gutenberg project and Wikisource.
The Bibliothèque nationale de France (BnF) has an even larger
collection of poems since it is in charge of legal deposit for France. A large proportion of these books has been
digitized and is available on the Gallica website (maintained by the BnF). The BnF was thus able to select and
extract a large number of poetry books, which included various collections, anthologies and essays (all the data
are in the XML Alto format). We selected the books with an OCR quality score above 98%, and used the BnF API to
collect metadata about the books.
As these are complete books, not everything in them was relevant. Some books were simply irrelevant (e.g.,
critical essays that do not contain poetry), some parts had to be removed (preface, introduction, critical notes)
and, even once we had reduced the text to poetry, we still needed to extract sonnets. In order to do this, several
heuristics were used, thanks to Python scripts aiming at retrieving poems in the form: two quatrains followed by
two tercets (the form of a sonnet). This heuristic (based simply on the analysis of space and empty lines between
verses) proved quite robust and efficient, even if not perfect. Thanks to the resource provided by the BnF, we were
able to considerably increase the number of sonnets in the database, with relatively few errors according to our
estimation.
As a result, the Oupoco Database is a collection of 4,872 French sonnets. 760 different authors are represented:
4,414 sonnets written by men (660 different authors), and 439 sonnets written by women (107 authors), which leaves
19 sonnets to which we have not been able to assign an author. A specific license related to the source they come
from is attached to all the sonnets, but all are freely available and can be reused for free (under the Creative
Commons Attribution 4.0 International license), see
Table 1.
Source |
Number of Sonnets |
License/Comments |
BnF |
3,979 |
CC-BY-SA-NC |
Wikisource |
772 |
CC BY-SA 3.0 |
Web |
67 |
Source (Blog) cited in the database |
Books (anthology) |
37 |
Manual collections of sonnets from different anthologies |
Malherbe project |
7 |
No explicit license (https://git.unicaen.fr/malherbe/corpus) |
Table 1.
Sources of the sonnets in the corpus
This database can be used for various teaching and research purposes, especially in the following domains:
literature studies, corpus linguistics, digital humanities, arts and technology. All major French poets from the
19th century are included in the database, but also some lesser known ones. Each sonnet is encoded in XML format
along with the related metadata; a TEI version of the database is publicly available (for further explanation and
access to the source files, see our data paper [
Mélanie-Becquet et al 2022] and the related Zenodo repository:
https://zenodo.org/deposit/5646940).
4 Rhyme Analysis
The OuPoCo project has nothing to do with the recent neural approach to poetry generation [
Ghazvininejad et al 2017]
[
Van de Cruys 2020], but it does require accessing a formal representation of rhymes (as proposed by
Beaudouin in
2002[4]). We will not detail here the (complex) rules of French versification, but two
main difficulties need to be mentioned. First, as is widely known, pronunciation and spelling differ greatly in
French, as in English. There is thus a need to first transform written texts into a phonetic transcription. Second,
French has a specific and quite complex versification system, which is different (and far more complex) than simple
phonetics. The second stage consists then in transforming the phonetic transcription into a representation that
corresponds to French versification rules.
In order to do this, the first step is to produce a phonetic transcription of the last word of each line.
Phonetization (the process of transforming a word into a phonetic transcription) was done with eSpeak, a free
software available on the Web (
http://espeak.sourceforge.net),
that provided satisfactory results on our data. We analyze the whole verse and not only the last word of each line,
so that a full rhythmic analysis is possible. However, the phonetic transcription provided by eSpeak is not
enough.
It is not enough because not everything that has the same sound in French can rhyme: this is, in a way, the beauty
of poetry, and specific rules have to be defined to go from a phonetic transcription to a representation that
corresponds to the rules of versification. Let’s take an example. The two words aimé and aimée have the same phonetic transcription, but do not
rhyme, according to French versification rules (masculine and feminine words, in this case words that end with -é,
as opposed to -ée, do not rhyme); there are also cases where the phonetic transcription is slightly different but
the words actually rhyme (for example words ending with the sounds [e] and [ε]). All these cases are relatively
frequent and must be handled appropriately.
A series of rules written in Python had thus to be defined to obtain a proper analysis of rhyme derived from the
phonetic transcription (especially of the last word of each line). These rules were manually defined and
maintained, as there is no way they could be learnt directly from the data. Some of the rules can be easily derived
from a treatise on French versification, but others are directly linked to the output of eSpeak, as we have to
overwrite some phonetic distinctions produced by this software that are not relevant to analyze poetry.
The sonnet generator uses this analysis to produce sonnets, with different possible structures, respecting the
rules of French versification (the code and the resources used, especially the sonnet database, are open source and
freely available for research, see:
https://github.com/clement-plancq/oupoco-api).
5 Constraints on the Generation Process
In the footsteps of Oulipo and following the comments of Queneau who did not like the
idea of purely random poetry generation, we chose to implement constraints to enable the reader to interact with
the database, control the generation process in different ways, and discover 19th century French literature from a
different and more playful angle.
The first constraint corresponds to the different forms of sonnets that have been proposed in the course of
history. Giacomo da Lentini, Petrarch, Marot, Peletier, Shakespeare and Spenser all proposed and initiated slightly
different rhyming schemes (for example, Marot proposed the following structure: ABBA ABBA CCD EED, while Petrarch
proposed several slightly different structures: ABBA ABBA CDE CDE / ABBA ABBA CDC DCD / ABBA ABBA CDE DCE, etc.).
All these forms of sonnets are available and the user can choose any structure s/he prefers for generation.
The second constraint enables the reader to generate random sonnets from texts within a chosen time framework. In
other words, if the reader selects a period of twenty or thirty years that s/he wants to explore on the timeline,
sonnets will be generated according to this time frame. This option makes it possible to have a quick overview of
the productions of French sonnets over a period. Thanks to this option, it is for example possible to note that
very few French sonnets were written at the beginning of the 19th century while their production tended to increase
20 years or so later.
The third constraint deals with the authors themselves. The reader can select one or several poets as the source
corpus to generate new sonnets. It is thus possible to explore the poems written by Baudelaire for instance, or to
combine them with those written by Rimbaud or Verlaine.
The fourth constraint is based on a semantic analysis of the original sonnets. Six main topics were identified
(beauty, love, death, melancholy, nature, spirituality), later on reduced to five, as melancholy and death were
hard to distinguish (beauty and love are also very close from a linguistic point of view, as well as death and
spirituality, but they are nevertheless different enough to be annotated and recognized with sufficient accuracy).
A sample of sonnets was annotated using these categories (50 sonnets per category) and a classifier was
subsequently trained on the resulting manually annotated corpus. It is thus possible to generate sonnets on a
specific topic. Note that the annotation operates at the sonnet level, whereas generation operates at the level of
the individual line of verse. However, we assume that the theme gives a general flavor to the text, and that not
every line has to be relevant from a thematic point of view
This annotation is however highly subjective. Sometimes most of the poem is on a specific topic, while the last
line gives a completely different perspective. See for example Le dormeur du
val, by Rimbaud. This poem is highly bucolic, clearly about nature since it is about a man peacefully
sleeping in a field — except that the last line completely changes the whole perspective, by revealing that the man
is in fact a dead soldier. In cases like this, we chose to annotate the dominant topic (the one which covers most
of the poem), “nature” in this case (but “death” would also have been relevant, and maybe more relevant
if we take into account the deep meaning of the sonnet). All this reveals the subjectivity of any annotation.
During the experiment, inter-annotator agreement was not high, but still acceptable and far beyond chance.
In the end, all these constraints are available through a very simple interface on the project web site.
Figure 5 gives an overview of this interface. The more constraints one chooses, the
fewer the potential sonnets generated (basically, each constraint restricts the possible choices and therefore the
number of lines available for generation).
From a computational point of view, the approach is quite simple. However, it is difficult to control on the fly
the number of sonnets that can be generated, depending on the number of constraints chosen by the end user. It is
however important to keep track of this, otherwise the end user may frequently arrive at a dead end, with a number
of constraints that prevents the possibility of generating new sonnets (a basic rule being that a line cannot rhyme
with itself, and cannot be selected twice).
Lastly, we wanted to take gender into account, and highlight female authors, who are underrepresented in most
poetry anthologies. A special effort was made to identify sonnets by female authors, as the initial corpus (from
Wikisource) contained mostly male authors. Finally, thanks to the data extracted from the BnF corpus and to
intensive manual work, we were able to identify 439 sonnets written by 107 female authors (see
section 3). This was enough to produce a specific system highlighting the creativity of
the female authors, most of whom had remained in the dark so far. The system is available on the Oupoco web site,
in a specific tab
[5], see
Figure 6.
6 Evaluation
Poetry is, by nature, hard to evaluate. We did not perform a formal evaluation, as we were unable to provide
meaningful evaluation criteria [
Gervas 2013]. In our case, the first thing to be done was simply to
examine some poems produced by the system, and assess their quality. Due to the nature of the generative process,
the generated poems make more or less sense, and are more or less pleasant to read.
We identified different causes that affect the quality of the text produced, mainly related to syntax. The most
frequent issues are: a pronoun that cannot be linked to any other element in the sentence, or a segment that does
not fit with the preceding part of the sentence. Both situations reveal in fact the same problem: one cannot obtain
a coherent text simply by assembling smaller chunks of text obtained randomly. This was already one of the main
problems of statistical machine translation (based on segments of text that the system had to assemble to form full
sentences, see Poibeau (
2017): because of the limitations of the approach, the
resulting sentences were often slightly incorrect and grammatically odd. This has been largely solved with the
modern neural approach, since it is now possible to encode full sentences directly (through vectors and deep
learning approaches).
But let’s come back to our system and examine a specific example. The following poem was fully automatically
produced by our system (emphasis by color difference added by the authors).
Les vendangeurs lassés ayant rompu leurs lignes,
La trirème d’argent blanchit le fleuve noir
Sachant que notre cœur s’emporte et se résigne,
Étranger tes sanglots dans le fatal mouchoir.
C’est par un ciel pareil, tout blanc du vol des cygnes,
L’éclair laisse, en fuyant, l’horizon triste et noir.
Je hais le mouvement qui déplace les lignes,
Et son verger fleuri n’est qu’un vaste encensoir.
Mais, le corps étendu, n'oublions pas que l'âme,
Ils me rendent aveugle au jour qui te proclame
Si proche et déjà loin de celui que j’aimais.
Haute théologie et solide morale,
Et maintenant j’habite, hélas! et pour jamais,
S’envole, tinte et meurt dans le ciel rose et pâle.
Any native reader of French will be disturbed by things such as ils (they) in the third tercet, that cannot be related to anything in the
surrounding text. In the first quatrain, étranger would fit as an apostrophe, but the
rest of the line (…tes sanglots…) show that the noun cannot be interpreted as an
apostrophe and, in fact, the whole line cannot be linked to what precedes. The same situation arises in the second
quatrain (where l’éclair laisse, en fuyant… cannot be attached to the surrounding text),
and again in the last tercet (s’envole, tinte et meurt needs a subject that cannot be
found in the text).
All these are clear examples that violate syntax and make the whole poem odd and clearly not the result of human
inspiration. It is a pity because otherwise, from a semantic point of view, there are some signs of coherence in
the fact that the same topics can be found in the different lines. For example, in the second quatrain, le ciel (the sky), l’horizon (the
horizon), les lignes (the lines) all refer to the vast
surroundings of the poet, whereas vol des cygnes (flight of swans), l’éclair (lightning) and
le verger (the orchard) are clear allusions to nature. Even in the first
quatrain, a link could be established between les sanglots (sobs), le mouchoir (the handkerchief), and le fleuve noir
(the black river), and notre cœur [qui] s’emporte et se résigne
(our heart [that] gets carried away and is resigned), all this being of course signs of sadness.
We did not try to solve these issues, for example the syntactic incoherencies. Solving them would considerably
complexify the system, which we wanted to keep as simple as possible. Note also that the more constraints there
are, the more the number of available lines at each position is reduced. Lastly, working on these issues would
involve implementing many heuristics without any clear scientific benefit (except that of producing better poems,
which one could say is the main goal, though).
The most obvious approach would be to move to neural poetry generation (a completely different approach), which we
have explored but decided not to include in this system for the reasons given above: it would complexify the whole
architecture and, for example, would require a GPU for training and for testing (as well as for the system in
production). We considered that it was more interesting and more promising to explore neural poetry generation
separately, as a new system and a new domain of research. We will not address this here as it is beyond the scope
of this paper.
7 Collaboration with Artists
From the beginning, Oupoco was not just an engineering or a research project. Because the project deals with
poetry, and because its main objective is to interest people in it, it was important to go beyond a pure algorithm,
and also to offer new ways to access poetry.
Queneau designed his book as an object, as a device that the reader can manipulate, with which the
reader can interact and produce her/his own poetry. It was thus important to us to also materialize the project
through an innovative device that would be both intriguing and appealing. In order to do this, we collaborated with
two artists who belong to a collective called Atelier Raffard-Roussel. This is what they say
themselves about this project and this collaboration:
[6]
We intervened in [the Oupoco Project] to propose a work that could give this research a new
form of visibility and materiality.
To do this, we made a simple device that allows a user to generate a poem automatically by turning a crank. Via
a small peripheral screen, the user is also informed of the amount of electrical energy that was required to
generate this new poem. If they wish, they can try to guess how the Poetry Box works
through the transparent walls.
This device, which is both mechanical and electronic, is a direct reference to Hans Haacke's Condensation Cube, which can be considered a milestone work of American conceptual art,
and which is almost contemporary with Raymond Queneau's book, since it was made in 1965. It seems to
us that there is a great similarity between these two works in that each of them reacts, so to speak, to the
conditions of their exhibition; the Condensation Cube produces water vapour
according to the humidity of the place in which it is exhibited and Queneau's book produces poems
according to the luck and mood of the reader.
This project was an opportunity for us to tackle the creation of an object that could be both a machine and a
work of art and to reflect on the ecological issues involved in such a practice. What is machine-like in works of
art and what is sculpture-like in the machines that surround us? How can we make the environmental impact of
building a machine or a work of art more visible?
The resulting device, the
Boîte à poésie (
Poetry
box), is pictured on
Figure 7.
The Poetry Box is a very relevant tool to perform public demonstrations, as it is
both portable and appealing. The object is also intriguing, since it is transparent and reveals the cables and
computer cards (all Raspberry Pi components) it is made of. This proved to be a very efficient tool to engage the
public with poetry.
In addition to this portable device, we also developed a Twitter bot that posts a quatrain every 6 hours (
Figure 8).
We also released, in collaboration with Riva Illustration a short movie, which explains the project, the approach
and the
Boîte à poésie[7]. This short movie
is an essential element in the dissemination of our work. It can be consulted online, at any time, without
restrictions. It is available in English and in French. This short movie was awarded the prize for “the most
entertaining video” during the IJCAI 2023 conference in Macao
[8] (IJCAI, the 32nd International Joint Conference on Artificial Intelligence, is one of the most
prestigious international conferences in Artificial intelligence).
These different devices (web site, short movie, Boîte à poésie, Twitter
bot, etc.) make it possible to propose different kinds of demonstrations, to different audiences, in different
settings. They also proved useful to make the project more popular.
8 Demonstrations and engagement with the public
At the crossroads between surrealism and absurdism, generated sonnets are generally quite funny and convey a
dreamlike atmosphere. The themes specific to the Romantic period – such as love, whether it is magnified or lost,
death or the fleetingness of time to name but a few – contribute to creating bizarre but intriguing poems. While
most of them lack coherence, particularly with respect to the use of punctuation or pronouns, the syntactic
confusions this creates can actually reinforce their poetic overtones. The Oupoco system is intended to be
presented in front of an audience, to elicit reactions, as a means to make people rediscover poetry and
literature.
8.1 Demonstrations
We gave several demonstrations of the Oupoco project, to different audiences. A number of these presentations
occurred online, because of the Covid pandemic. Oupoco was mostly developed between 2018 and early 2020, so
became available just at the beginning of the pandemic, which greatly impacted the number of demonstrations we
were able to do. However, we seized the opportunities to present the project to researchers and librarians (for
example thanks to meetings organized by the French national library, especially during the “Content Generative Models and GLAM” workshop organized by the AI4LAM network, on “artificial
intelligence in, for and by libraries, archives and museums”, on 19/04/2022) and also to a wider audience
through the participation in open days (at the Ecole normale supérieure and the University Paris Science et
Lettres) and science festivals. Demonstrations for researchers were made using traditional presentations on a
computer, but the Boîte à poésie was the main support for open days
and science festivals.
8.2 Reactions
The main goal of the project, beyond the scientific challenge of automatically analyzing rhymes and detecting
the main topic of a poem, was to interest people in poetry and literature in a non-academic way. Reactions were
generally very positive and enthusiastic. We did not perform a comprehensive study, but we discuss here some of
the observations we made during these demonstrations.
Because the machine produces structurally impeccable sonnets, the experiencer is unconsciously encouraged to
find coherence in them, simply because we are used to coherence in our everyday life and because incoherence is
bewildering [
Reinhart 1980]. The second observation we made (which follows on from the previous one
to some extent), is a frequent need for the experiencer to go back to the original poem, to see where a given
line comes from (on the Oupoco website, “tooltips” always allows the experiencer to go back to the original
sonnet). This is encouraging as our main goal is to re-engage people with poetry (showing that poetry is
interesting, and surprising).
Other reactions were more surprising. Some children were fascinated by the Boîte à poésie and the cables inside the object. The fact that computers are made of electronic cards
and cables is obvious to us, but computers remain abstract objects for children who have never seen “inside the
box”. This experience was a way to explain to them that a computer manipulates information through
electricity and that data and programs have to be physically stored somewhere, inside the machine.
Last but not least, although we were not able to do many demonstrations in schools due to the pandemic, several
people told us that the
Boîte à poésie, beyond engaging pupils and
students with poetry, was also a very good way to raise their awareness of complex linguistic issues such as text
coherence. The program frequently produces non optimal texts (with pronouns not referring to any antecedents or
with erratic syntactic constructions, as shown in
Section 6). Since these texts
are produced by a machine, there is no harm in using them to explain why they are problematic, and how they could
be improved. The whole process also helps to show that a computer is not perfect in itself: it is just the result
of what people (especially, programme designers) do with it.
8.3 Objections
Even if most of the reactions about the website or about the Boîte à
poésie were positive, we also had to face a few reservations, generally from teachers and professors of
French literature. Their worries concerned the image all this gives of literature, and more specifically poetry.
By assembling lines of verse selected from different poems (either randomly or with the light supervision of the
reader) one may often produce meaningless texts. This could lead the reader to think that poetry can be anything,
that even meaningless text or just a bunch of random words put together can be poetry. In brief, people could
lose the sense of what real poetry is.
While this has to be taken into account, our experience showed that people are well aware of what we propose
through this system. Everybody immediately understood that the sonnets were generated automatically and that they
do not have to make sense. In other words, they are not real poems and cannot be confused with poems written by
humans. Conversely, as explained in the previous sections, people were often puzzled and wanted to know the
source of a given line, and wanted to have a look at the original poem. So, far from being a distraction, the
system was a way to reconcile people with poetry, although on a very limited and modest scale. We do not think
our system will fundamentally change how people see poetry (a genre with a very limited number of readers
nowadays, unfortunately), but it could at least arouse curiosity for this literary genre.
In our opinion, the project is thus not a sacrilege with respect to venerated texts, but a way to make people
experience and rediscover poetry.
9 Discussion
Now that we have described the project in detail, it may be interesting to come back to the rationale behind this
project. What have we explored, what have we learnt in the end, beyond developing a piece of software and some
devices inspired by Queneau? How should we apprehend the poems created by the machine?
As said in the beginning, one piece of inspiration was Kenneth Goldsmith’s book
Uncreative
writing (
2011). Goldsmith contends that the vast reservoir of
pre-existing texts available in digital form allows people (especially writers) to engage with language in novel
ways, emphasizing the value of recontextualization and reinterpretation over the creation of entirely new content.
This approach challenges conventional ideas about what constitutes originality and innovation in the realm of
writing and highlights the evolving relationship between humans and text. Goldsmith provocatively advocates for a
shift towards a more "uncreative" approach to writing. He posits that human creativity can also be found in the act
of appropriating and remixing existing texts, blurring the lines between authorship and readership. We partly
wanted explore this idea through the Oupoco project.
This may also remind the reader of Charles O. Hartman’s book,
Virtual Muse: Experiments in
Computer Poetry (
1996). In this book, Hartman explores technology and
literature, showcasing the transformative potential of computers in redefining the very essence of poetry. Through
meticulous analysis and experimentation, he demonstrates how algorithms and computational processes can be
harnessed to generate innovative and unexpected poetic forms, challenging established norms and expanding the
horizons of creative expression. More specifically, his first experiment was in a way a precursor of our own: a
program named “RanLines” was designed to store a collection of 20 lines and subsequently
to fetch one of these lines at random whenever the user pressed a key, so as to produce a kind of poem. Through
this program, the author explores a “simple sort of
randomness” that reminds him of the Greek oracles.
What is even more interesting are Hartman’s reflections on the results he got. He observed that “It’s hard to put together two words that don’t make some kind of sense to the willing
reader” [
Hartman 1996, 31]. He also adds that: “The more discrete and self-contained the syntax of the line (complete clause, complete
prepositional phrase), the more easily it joins with lines before and after”, which is also what we
observed, and one of the limits of our experiments (when a linguistic element refers to other ones outside the
line, coherence – or simple linguistic well formedness – is often lacking). But beyond this issue, we agree with
Hartman that these experiments open new perspectives to the willing reader. As Hartman suggests, the reader’s
imagination is challenged, as it is nearly always possible to find some meaning, draw some connexions and interpret
combined verses. At the same time, our experiments showed that the application is also a strong incentive to
rediscover poetry: very often, people are intrigued by a line and want to go back to the original poem.
To conclude, we can say we have explored in a new manner the idea of potential literature, by producing new
sonnets from a very well-defined set of constraints, following in this sense the program put forward by
Queneau more than 60 years ago.
10 Conclusion
The main interest of the Oupoco project is to present French poetry through a new and original setting. With our
system, poetry is not just a literary genre, but a dynamic object that can be manipulated and experienced. For many
people, poetry is seen at best as something related to school education, at worst as something boring and
uninteresting from the past. Our new setting, in itself, makes it possible to show that playing with poetry can be
fun. Our setting puts the notion of text coherence in perspective since the result of the generator can be more or
less satisfactory from a semantic point of view [
Reinhart 1980]. In the future, we plan to study the
potential impact of our system in different (real world) contexts, especially in educational settings.
Acknowledgements
This work received support from EUR Translitterae (Ecole universitaire de recherche, program “Investissements d’avenir” ANR-10-IDEX-0001-02 PSL* and ANR-17-EURE-0025) and from the CNRS
through the International Research Network Cyclades (Corpora and Computational Linguistics for Digital Humanities).
This work was also supported in part by the French government under the management of the Agence Nationale de la
Recherche as part of the “Investissements d’avenir” program, reference
ANR19-P3IA-0001 (PRAIRIE 3IA Institute).
Author Roles
- Frédérique Mélanie-Becquet: conceptualization, data curation and supervision
- Clément Plancq: conceptualization and software development
- Claude Grunspan: data curation
- Mylène Maignant: conceptualization and data curation
- Matthieu Raffard: conception and development of the Poetry Box (Boîte à poésie)
- Mathilde Roussel: conception and development of the Poetry Box (Boîte à poésie)
- Fiammetta Ghedini: conception and development of the Oupoco video clip
- Thierry Poibeau: conceptualization, funding acquisition, supervision and writing
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