Relevant bibliographies by topics / Computer generated poetry

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  1. Journal articles
  2. Dissertations / Theses
  3. Book chapters
  4. Conference papers

Academic literature on the topic 'Computer generated poetry'

Author: Grafiati
Published: 4 June 2021
Last updated: 3 February 2022

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Journal articles on the topic "Computer generated poetry"

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Yi, Xiaoyuan, Ruoyu Li, Cheng Yang, Wenhao Li, and Maosong Sun. "MixPoet: Diverse Poetry Generation via Learning Controllable Mixed Latent Space." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 05 (2020): 9450–57. http://dx.doi.org/10.1609/aaai.v34i05.6488.

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As an essential step towards computer creativity, automatic poetry generation has gained increasing attention these years. Though recent neural models make prominent progress in some criteria of poetry quality, generated poems still suffer from the problem of poor diversity. Related literature researches show that different factors, such as life experience, historical background, etc., would influence composition styles of poets, which considerably contributes to the high diversity of human-authored poetry. Inspired by this, we propose MixPoet, a novel model that absorbs multiple factors to create various styles and promote diversity. Based on a semi-supervised variational autoencoder, our model disentangles the latent space into some subspaces, with each conditioned on one influence factor by adversarial training. In this way, the model learns a controllable latent variable to capture and mix generalized factor-related properties. Different factor mixtures lead to diverse styles and hence further differentiate generated poems from each other. Experiment results on Chinese poetry demonstrate that MixPoet improves both diversity and quality against three state-of-the-art models.
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Beckett, C. "Translating poetry: Creative art or semantic science? A case study." Literator 21, no. 3 (2000): 75–90. http://dx.doi.org/10.4102/lit.v21i3.498.

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There is an on-going debate as to the real value of translation: is it an art or a science? Is the translator engaged in genuine creation or is she merely transliterating the creation of someone else? In order to attempt to resolve this long-standing and thorny problem, this article examines the poet’s understanding of the “logos", the creative force of the word and the relationship which exists between the “signifiant" and the “signifié”. Extracts from poems by Alan Paton, Victor Hugo and Pablo Neruda serve to illustrate that poetic words not only transmit the poet’s experience but actually create it. If the poet is sensitive to the creative nature of language, as these two extracts suggest he should be, it follows logically that a good translator too must be aware of the degree to which language can create, and this perception must be implemented in the subsequent translation. Because only human beings and not machines possess sensitivity, it stands to reason that a machine is incapable of effectively translating the most emotional of literary genres: poetry. So as to illustrate this fact, this article compares and contrasts a computer-generated translation of Paul Verlaine's poem “Chanson d’automne" with three “human-generated” translations. In my own translation, comments and justifications are made as to the choice of a particular word or phrase proposed as translation. The conclusion is reached that translation implies a high degree of sensitivity towards the poet’s original intention as well as a collaborative process between poet and translator which results in an entirely new poem which involves as much, but different creativity as the original writing of the poem.
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Köbis, Nils, and Luca D. Mossink. "Artificial intelligence versus Maya Angelou: Experimental evidence that people cannot differentiate AI-generated from human-written poetry." Computers in Human Behavior 114 (January 2021): 106553. http://dx.doi.org/10.1016/j.chb.2020.106553.

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Schwartz, Oscar. "Competing Visions for AI." Digital Culture & Society 4, no. 1 (2018): 87–106. http://dx.doi.org/10.14361/dcs-2018-0107.

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Abstract In this paper, I will investigate how two competing visions of machine intelligence put forward by Alan Turing and J. C. R Licklider - one that emphasized automation and another that emphasized augmentation - have informed experiments in computational creativity, from early attempts at computer-generated art and poetry in the 1960s, up to recent experiments that utilise Machine Learning to generate paintings and music. I argue that while our technological capacities have changed, the foundational conflict between Turing’s vision and Licklider’s vision plays itself out in generations of programmers and artists who explore the computer’s creative potential. Moreover, I will demonstrate that this conflict does not only inform technical/artistic practice, but speaks to a deeper philosophical and ideological divide concerning the narrative of a post-human future. While Turing’s conception of human-equivalent AI informs a transhumanist imaginary of super-intelligent, conscious, anthropomorphic machines, Licklider’s vision of symbiosis underpins formulations of the cyborg as human-machine hybrid, aligning more closely with a critical post-human imaginary in which boundaries between the human and technological become mutable and up for re-negotiation. In this article, I will explore how one of the functions of computational creativity is to highlight, emphasise and sometimes thematise these conflicting post-human imaginaries.
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Frawley, Jessica Katherine, and Laurel Evelyn Dyson. "Literacies and Learning in Motion." International Journal of Mobile and Blended Learning 10, no. 4 (2018): 52–72. http://dx.doi.org/10.4018/ijmbl.2018100104.

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Mobile and participatory cultures have led to widespread change in the way we communicate; emphasizing user generated content and digital multimedia. In this environment, informal learning may occur through digital and networked activities, with literacy no longer limited to alphabetic and character-based texts. This article explores adult learners' new literacies within the context of a digital mobile storytelling project. A qualitative approach is used to explore the artifacts and practices of nine adult participants who comprise the study. Participants created a range of fiction, non-fiction, poetry and diary-style content in a variety of modes and media. Outcomes from content analysis, interview and survey methods depict mobile digital literacies as characteristically situated, experiential and multimodal. The mobile and participatory nature of this project was catalytic to participants' imaginative re-interpretation of the world around them as sources for meaning making and transformation. This paper contributes a case example of mobile learning with adults in a community setting.
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Zhang, Richong, Xinyu Liu, Xinwei Chen, Zhiyuan Hu, Zhaoqing Xu, and Yongyi Mao. "Generating Chinese Ci with Designated Metrical Structure." Proceedings of the AAAI Conference on Artificial Intelligence 33 (July 17, 2019): 7459–67. http://dx.doi.org/10.1609/aaai.v33i01.33017459.

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Ci is a lyric poetry form that follows highly restrictive metrical structures. This makes it challenging for a computer to compose Ci subject to a specified metrical requirement. In this work, we adapt the CVAE framework to automated Ci generation under metrical constraints. Specifically, we present the first neural model that explicitly encodes the designated metrical structure for Ci generation. The proposed model is shown experimentally to generate Ci with nearly perfect metrical structures.
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Tsur, Reuven, and Motti Benari. "‘Composition of place’, experiential set, and the meditative poem." Pragmatics and Cognition 9, no. 2 (2001): 203–37. http://dx.doi.org/10.1075/pc.9.2.03tsu.

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Meditative poetry has the ability to reproduce aspects of the meditative experience. In this paper we explore this ability, trying to clarify the phenomenon by pointing out the cognitive processes involved. We focus on Christian Jesuit meditation and pinpoint one of its most effective elements: “the composition of place”. We argue that three main abilities associated with “the composition of place” are responsible for the meditative quality detected in poetic meditative texts: The text’s ability to evoke an orientation process; the text’s ability to support diffuse perception and encourage divergent ways of processing; the text’s ability to generate the mental set required for this experience, the absence of purpose, and to supply the conditions that enable such a mental set to exist over time. We illustrate our theoretical discussion through a close reading of two meditative poetic masterpieces: Donne’s Holy Sonnet No. 7, and the Spanish anonymous sonnet “A Cristo Crucificado”.
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Fritz, Darko. "Vladimir Bonačić: Computer-Generated Works Made within Zagreb's New Tendencies Network (1961–1973)." Leonardo 41, no. 2 (2008): 175–83. http://dx.doi.org/10.1162/leon.2008.41.2.175.

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Scientist Vladimir Bonačić began his artistic career in 1968 under the auspices of the international New Tendencies movement (NT). From 1968 to 1971 Bonačić created a series of “dynamic objects”—interactive computer-generated light installations, five of which were set up in public spaces. The author shows the context of Bonačić's work within the Zagreb cultural environment dominated by the New Tendencies movement and network (1961–1973). The paper shows his theoretical and practical criticism of the use of randomness in computer-generated art and describes his working methods as combining the algebra of Galois fields and an anti-commercial approach with custom-made hardware. It seems that Bonačić's work fulfills and develops Matko Meštrović's proposition that “in order to enrich that which is human, art must start to penetrate the extra-poetic and the extra-human.”
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Cheok, Adrian David, Owen Noel Newton Fernando, Janaka Prasad Wijesena, et al. "BlogWall: Social and Cultural Interaction for Children." Advances in Human-Computer Interaction 2008 (2008): 1–8. http://dx.doi.org/10.1155/2008/341615.

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Short message service (SMS) is extremely popular today. Currently, it is being mainly used for peer-to-peer communication. However, SMS could be used as public media platform to enhance social and public interactions in an intuitive way. We have developed BlogWall to extend the SMS to a new level of self-expression and public communication by combining art and poetry. Furthermore, it will provide a means of expression in the language that children can understand, and the forms of social communication. BlogWall can also be used to educate the children while they interact and play with the system. The most notable feature of the system is its ability to mix up and generate poetry in multiple languages such as English, Korean, Chinese poems, or Japanese “Haiku” all based on the SMS. This system facilitates a cultural experience to children unknowingly, thus it is a step into new forms of cultural computing.
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Panchenko, Daria V. "Visual metaphors as a vector of the poetic text analysis." Literature at School, no. 2, 2020 (2020): 98–108. http://dx.doi.org/10.31862/0130-3414-2020-2-98-108.

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Digital technologies continue to change the modern human’s perception, especially intensively affecting the younger generation. The most serious manifestation of the ongoing processes was the cultural request for effects, not meanings, formed at the turn of the XX–XXI centuries. In this regard, literature as an art that generates and conveys meanings is rapidly losing its relevance and value among young people. However, digital art, a modern computer graphic that fascinates the Internet users and especially adolescents with its emphasized effect, is quite capable of serving literature as a kind of guide to the word, as it contains a large number of metaphors that are “synonymous” to the poems included in the school literary education curriculum. This article is devoted to the search for new ways of “reading” and understanding texts through visual images. The purpose of the article is to consider the possibilities of using digital visual formats while teaching literature. The material used for the research is the work of designers and digital artists on the popular Internet photo hosting sites: visual metaphors. The main research methods are theoretical (analysis of philosophical, literary sources in accordance with the methodological setting of the study) and experimental (testing the developed educational material in literature lessons). When studying poetry, the article proposes to include in the content of the lessons the analysis of the artistic imagery of metaphors from the standpoint of literature and pictoriality as a new means of modern communication. The author describes in detail the example of the study of A.S. Pushkin’s poem “The Prophet” and an excerpt from V.V. Mayakovsky’s poem “A Cloud in Trousers”, within the framework of which visual metaphors act as the vector of analysis, leading to a comparison of texts and design artwork, the identification of additional meanings that enrich the understanding of images, and a holistic interpretation of works.
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Dissertations / Theses on the topic "Computer generated poetry"

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Peterson, Cole. "Generating rhyming poetry using LSTM recurrent neural networks." Thesis, 2019. http://hdl.handle.net/1828/10801.

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Current approaches to generating rhyming English poetry with a neural network involve constraining output to enforce the condition of rhyme. We investigate whether this approach is necessary, or if recurrent neural networks can learn rhyme patterns on their own. We compile a new dataset of amateur poetry which allows rhyme to be learned without external constraints because of the dataset’s size and high frequency of rhymes. We then evaluate models trained on the new dataset using a novel framework that automatically measures the system’s knowledge of poetic form and generalizability. We find that our trained model is able to generalize the pattern of rhyme, generate rhymes unseen in the training data, and also that the learned word embeddings for rhyming sets of words are linearly separable. Our model generates a couplet which rhymes 68.15% of the time; this is the first time that a recurrent neural network has been shown to generate rhyming poetry a high percentage of the time. Additionally, we show that crowd-source workers can only distinguish between our generated couplets and couplets from our dataset 63.3% of the time, indicating that our model generates poetry with coherency, semantic meaning, and fluency comparable to couplets written by humans.<br>Graduate
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Book chapters on the topic "Computer generated poetry"

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Yu, Hai, Zi-Xuan Li, and Yu-Yan Jiang. "Using GitHub Open Sources and Database Methods Designed to Auto-Generate Chinese Tang Dynasty Poetry." In Communications in Computer and Information Science. Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-7530-3_32.

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"Substitution Awe – Science Fiction Cinema and the Computer-Generated Mysterium Tremendum." In Tzedek, Tzedek Tirdof: Poetry, Prophecy, and Justice in Hebrew Scripture. BRILL, 2018. http://dx.doi.org/10.1163/9789004355743_011.

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Burrow, Colin. "Posthuman Postscript." In Imitating Authors. Oxford University Press, 2019. http://dx.doi.org/10.1093/oso/9780198838081.003.0012.

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The Postscript asks whether a machine could in the future successfully imitate a human poet. It discusses the history of artificially generated poems from early schoolroom manuals through John Clark’s ‘Eureka Machine’ of 1845 to the age of the computer. It relates Alan Turing’s ‘Imitation Game’, in which a computer mimics the linguistic behaviour of a human being, to a wider mid-twentieth-century tendency to see poetry as the ultimate challenge for an electronic imitator of human behaviour. The chapter argues that a computer which depended on statistical modelling of prior poetic corpuses would not be able to replicate the actions of a human imitator, because imitating authors imitate not simply words but practices, and those are not simply codifiable. Imitators do not simply follow the rules implicit in earlier texts, but might imitate an earlier author’s willingness to break those rules. The chapter shows that a pervasive opposition between biological and digital systems runs through writing about the possibility of artificially imitating human consciousness, which is the latest manifestation of the opposition between a ‘living’ recreation of a past author and a simulacrum. It concludes by discussing the Xenotext by the Canadian experimental poet Christian Bök, which seeks to create a perpetually living poetry engine embedded in the DNA of a permanently durable microbe. This takes the long-standing metaphor of a ‘living’ imitation to the cellular level, and makes of imitatio an unending biological process of transformation.
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Conference papers on the topic "Computer generated poetry"

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McGregor, Stephen, Matthew Purver, and Geraint Wiggins. "Process Based Evaluation of Computer Generated Poetry." In Proceedings of the INLG 2016 Workshop on Computational Creativity in Natural Language Generation. Association for Computational Linguistics, 2016. http://dx.doi.org/10.18653/v1/w16-5508.

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Fusu, Elena-Casiana, and Mihai-Lica Pura. "ROetry: First Steps Towards Computer Generated Poetry in Romanian Language." In 2020 12th International Conference on Electronics, Computers and Artificial Intelligence (ECAI). IEEE, 2020. http://dx.doi.org/10.1109/ecai50035.2020.9223175.

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Yi, Xiaoyuan, Maosong Sun, Ruoyu Li, and Zonghan Yang. "Chinese Poetry Generation with a Working Memory Model." In Twenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18}. International Joint Conferences on Artificial Intelligence Organization, 2018. http://dx.doi.org/10.24963/ijcai.2018/633.

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As an exquisite and concise literary form, poetry is a gem of human culture. Automatic poetry generation is an essential step towards computer creativity. In recent years, several neural models have been designed for this task. However, among lines of a whole poem, the coherence in meaning and topics still remains a big challenge. In this paper, inspired by the theoretical concept in cognitive psychology, we propose a novel Working Memory model for poetry generation. Different from previous methods, our model explicitly maintains topics and informative limited history in a neural memory. During the generation process, our model reads the most relevant parts from memory slots to generate the current line. After each line is generated, it writes the most salient parts of the previous line into memory slots. By dynamic manipulation of the memory, our model keeps a coherent information flow and learns to express each topic flexibly and naturally. We experiment on three different genres of Chinese poetry: quatrain, iambic and chinoiserie lyric. Both automatic and human evaluation results show that our model outperforms current state-of-the-art methods.
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Yang, Xiaopeng, Xiaowen Lin, Shunda Suo, and Ming Li. "Generating Thematic Chinese Poetry using Conditional Variational Autoencoders with Hybrid Decoders." In Twenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18}. International Joint Conferences on Artificial Intelligence Organization, 2018. http://dx.doi.org/10.24963/ijcai.2018/631.

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Computer poetry generation is our first step towards computer writing. Writing must have a theme. The current approaches of using sequence-to-sequence models with attention often produce non-thematic poems. We present a novel conditional variational autoencoder with a hybrid decoder adding the deconvolutional neural networks to the general recurrent neural networks to fully learn topic information via latent variables. This approach significantly improves the relevance of the generated poems by representing each line of the poem not only in a context-sensitive manner but also in a holistic way that is highly related to the given keyword and the learned topic. A proposed augmented word2vec model further improves the rhythm and symmetry. Tests show that the generated poems by our approach are mostly satisfying with regulated rules and consistent themes, and 73.42% of them receive an Overall score no less than 3 (the highest score is 5).
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