Using genetic algorithms to create meaningful poetic text

Work carried out when all authors were at the University of Edinburgh.Peer reviewedPostprin

Singing synthesis with an evolved physical model

A two-dimensional physical model of the human vocal tract is described. Such a system promises increased realism and control in the synthesis. of both speech and singing. However, the parameters describing the shape of the vocal tract while in use are not easily obtained, even using medical imaging techniques, so instead a genetic algorithm (GA) is applied to the model to find an appropriate configuration. Realistic sounds are produced by this method. Analysis of these, and the reliability of the technique (convergence properties) is provided

Generative sound art as poeitic poetry for an information society

This paper considers computer music in relation to broader society and asks what algorithmic composition can learn from the metaphysical shift which is happening in the so-called information societies. This is explored by taking the mapping problem inherent in the use of extra- musical models in generative composition and presenting a simple generative schema which prioritises sound, ex- ploiting the generative potential of digital audio. It is sug- gested that the exploration of such models has more than aesthetic relevance and that the interdisciplinary nature of digital sound art represents a microcosm of an emerging reality, thereby constituting a poietic playground for com- ing to terms with the implications and challenges of the information age

Topic Modeling and Figurative Language

Located at the center of Jorie Graham’s collection The End of Beauty, “Self Portrait as Hurray and Delay” crafts a portrait of the artist, poised at a precarious moment in which thought begins to take shape. Like Penelope, Graham entertains the illusion, if only momentarily, of a choice between bringing a creative impulse into form or allowing it to come undone. A weaver of language, Graham subtly, deftly, but unsuccessfully attempts to delay the inevitable moment in poetic creation in which complexity of thought adopts form through language, and so realized is also reduced. In The End of Beauty, the beginning of the creative act signals an inevitable descent into meaning – language’s ultimate impulse. Understanding how topic modeling algorithms handle figurative language means allowing for a similar beautiful failure – not a failure of language, but a necessary inclination toward form that involves a diminishing of language’s possible meanings. However, the necessarily reductive methodology of sorting poetic language into relatively stable categories, as topic modeling suggests, yields precisely the kind of results that literary scholars might hope for – models of language that, having taken form, are at the same moment at odds with the laws of their creation. In the following article, I suggest that topic modeling poetry works, in part, because of its failures. Somewhere between the literary possibility held in a corpus of thousands of English-language poems and the computational rigor of Latent Dirichlet Allocation (LDA), there is an interpretive space that is as vital as the weaving and unraveling at Penelope’s loom

Modern French Poetry Generation with RoBERTa and GPT-2

Peer reviewe