Portugal

Rosetta Code provides improv theatre performers with artificial intelligence (AI)-based technology to perform shows understandable across many different languages. We combine speech recognition, improv chatbots and language translation tools to enable improvisers to communicate with each other while being understood—or comically misunderstood—by multilingual audiences. We describe the technology underlying Rosetta Code, detailing the speech recognition, machine translation, text generation and text-to-speech subsystems. We then describe scene structures that feature the system in performances in multilingual shows (9 languages). We provide evaluative feedback from performers, audiences, and critics. From this feedback, we draw analogies between surrealism, absurdism, and multilingual AI improv. Rosetta Code creates a new form of language-based absurdist improv. The performance re- mains ephemeral and performers of different languages can express themselves and their culture while accommodating the linguistic diversity of audiences.

ICCC&#39;20

Rosetta Code: Improv in any language

improvisation

translation

multilingual

language models

stages 

COLING, the International Conference on Computational Linguistics, is one of the premier conferences for natural language processing and computational linguistics. Often grouped within the field of artificial intelligence, but actually pre-dating the development of artificial intelligence, advances in computational linguistics and natural language processing are now some of the major drivers behind the use of artificial intelligence for commercial and social applications – for example, on-line search, machine translation and with voice-assisted conversational devices.

First established in 1965, the biennial COLING conference is held in diverse parts of the globe and attracts participants from both top-ranked research centers and emerging countries. Today, the most important developments in our field are taking place not only in universities and academic research institutes, but also in industrial research departments and in technological startups. COLING conferences provide opportunities for all these communities to showcase their exciting developments.

COLING 2020

COLING, the International Conference on Computational Linguistics, is one of the premier conferences for natural language processing and computational linguistics. Often grouped within the field of artificial intelligence, but actually pre-dating the development of artificial intelligence, advances in computational linguistics and natural language processing are now some of the major drivers behind the use of artificial intelligence for commercial and social applications – for example, on-line search, machine translation and with voice-assisted conversational devices.

technical paper

Computational creativity is the art, science, philosophy and engineering of computational systems which, by taking on particular responsibilities, exhibit behaviours that unbiased observers would deem to be creative. As a field of research, this area is thriving, with progress in formalising what it means for software to be creative, along with many exciting and valuable applications of creative software in the sciences, the arts, literature, gaming and elsewhere.

The ICCC conference series organized by the Association for Computational Creativity since 2010 is the only scientific conference that focuses on computational creativity alone and also covers all aspects of it.


ICCC'20

The ICCC conference series organized by the Association for Computational Creativity since 2010 is the only scientific conference that focuses on computational creativity alone and also covers all aspects of it.
Computational creativity is the art, science, philosophy and engineering of computational systems which, by taking on particular responsibilities, exhibit behaviors that unbiased observers would deem to be creative. As a field of research, this area is thriving, with progress in formalizing what it means for software to be creative, along with many exciting and valuable applications of creative software in the sciences, the arts, literature, gaming and elsewhere.



"This paper introduces the notion ‘post-creativity’ as a reference point for discussing the ways in which the computational simulation of creativity perpetually seems to hinge upon conceptions of creativity that are both much-too-human and non-contingent. Taking issue with the often implicit idea within the artificial creativity-
agenda that creativity somehow exists before the fact, this paper, drawing upon Michel Foucault’s notion of the ‘dispositif’, insists that we must keep a steady eye on the historicity of the ideas and practices of ‘creativity’ in order to fully comprehend the ways in which computational/artificial creativity is part and parcel of the perpetual re-creation of creativity and hence, at best, contributing to a conceptual reverse-engineering of‘creativity’."

Post-creativity and AI: Reverse-engineering our Conceptual Landscapes of Creativity

In this presentation, we give an overview of the system that changes country flags based on trendy topics retrieved from news titles. 

Ever-changing Flags: Modifying National Symbols

The computational generation of visual representation of concepts is a topic that has deserved attention in Computational Creativity. One technique that is often used is visual blending – using two images to produce a third. However, visual blending on its own does not necessarily have a strong conceptual grounding. In this paper, we propose that visual conceptual blending be used for concept representation – a visual blend complemented by conceptual layer developed through elaboration. We outline a model for visual conceptual blending that can be instantiated in a computational system.

Let's Figure This Out: A Roadmap for Visual Conceptual Blending

Co-creative systems are useful in fostering creativity, often leading to unexpected results. Despite this, the relation between user and system is complex. The level of autonomy given to the system directly influences its potential for creative behaviour and degree of contribution to the cooperation with the user. In this paper, we present our efforts to instil a more creative behaviour to an existing visual blending system – Emojinating. In order to do so, we integrate two functionalities: self-evaluation and context-adaptation.

Emojinating Co-Creativity: Integrating Self-Evaluation and Context-Adaptation

"In this paper we consider the notion of dialogic creative ar- tificial intelligence (DCAI) systems, where co-creativity be- tween a human user and a computational system is supported through dialogic interaction. By dialogue we mean both tra- ditional language-based communication for explicit critique and persuasion (dialogue about creative artefacts) as well as a broader potentially non-linguistic notion of dialogue that emerges through the exchange of suggestions and changes (dialogue through creative artefacts). To capture this, we de- fine DCAI as occurring when both system and user are able to influence each others’ creative objectives. The paper mo- tivates our pursuit of dialogic interaction and provides some explanation of why we have defined it through its impacts rather than its mechanism of action. We provide two anal- yses to support our argument: an exploration of a commer- cial creativity support tool that has an extensive vocabulary for describing artefacts abstractly but does not meet our def- inition of dialogic interaction, and a case study of a creative interaction between two human professionals that exhibits di- alogic interaction throughout. For the latter we consider how studies of human-human co-creation can offer non-obvious design concepts that might be applied to co-creative DCAI systems.
"

A Speculative Exploration of the Role of Dialogue in Human-Computer Co-creation

We aim to help bridge the research fields of generative deep learning and computational creativity by way of the creative AI community, and to advocate the common objective of more creatively autonomous generative learning systems. We argue here that generative deep learning models are inherently limited in their creative abilities because of a focus on learning for perfection. To highlight this, we present a series of techniques which actively diverge from standard usage of deep learning, with the specific intention of producing novel and interesting artefacts. We end by describing how a two-way bridge between the research fields could be built.

Bridging Generative Deep Learning and Computational Creativity

Co-creativity research is thriving in a wide variety of domains, but we lack the vocabulary to talk about capabilities and progress across all those domains. We propose a framework to facilitate comparing how co-creative systems augment creativity. We draw on domain-agnostic concepts in interaction design research. Our framework describes the different aspects of interactions between one or more humans and their computationally creative collaborators at three levels: interaction modalities, interaction styles and interaction strategies.

Modalities, Styles and Strategies: An Interaction Framework for Human–computer Co-Creativity

This paper introduces EMILY, a machine that aims to createoriginal poems in the style of renowned poet Emily Dickin-son. Dickinson’s succinct and syntactically distinct style withunconventional  punctuation  makes  for  an  interesting  chal-lenge for automated poetry creation.  A user study comparesEMILY’s poems to Emily Dickinson originals, demonstratingthe machine’s ability to evoke mental images and highlight-ing challenges for future work.

EMILY: An Emily Dickinson Machine

Human collaboration with systems within the Computational Creativity (CC) field is often restricted to shallow interactions, where the creative processes, of systems and humans alike, are carried out in isolation, without any (or little) intervention from the user, and without any discussion about how the unfolding decisions are taking place. Fruitful co-creation requires a sustained ongoing interaction that can include discussions of ideas, comparisons to previous/other works, incremental improvements and revisions, etc. For these interactions, communication is an intrinsic factor. This means giving a voice to CC systems and enabling bi-directional communication channels between them and their users so that they can: explain their processes and decisions, support their ideas so that these are given serious consideration by their creative collaborators, and learn from these discussions to further improve their creative processes. For this, we propose a set of design principles for CC systems that aim at supporting greater co-creation and collaboration with their human collaborators.

Explainable Computational Creativity

Machines are used to be well-known for doing repetitive jobs, following code produced by humans, so not often imagined as capable of producing unexpected results without direct human intervention in each unique case. The generative art broke this boundary by incorporating random variables extracted from a natural phenomenon into the coded environment. Using this method, our project introduces physical laws into 3D printing instructions; a custom slicer and G-Code compiler were developed, allowing manipulation of Z-heights of extrusions from the 3D printer so gravity can be used to generate randomness in 3D outputs. As a result, unique organic and porous forms could be created from the 3D printing process, differing from traditional, watertight solid prints.

Rosetta Code: Improv in any language

Downloads

Next from ICCC'20

Post-creativity and AI: Reverse-engineering our Conceptual Landscapes of Creativity

Similar lecture

Neural Transduction for Multilingual Lexical Translation

Rosetta Code: Improv in any language

.css-70qvj9{display:-webkit-box;display:-webkit-flex;display:-ms-flexbox;display:flex;-webkit-align-items:center;-webkit-box-align:center;-ms-flex-align:center;align-items:center;}Downloads

Next from ICCC'20

Post-creativity and AI: Reverse-engineering our Conceptual Landscapes of Creativity

Similar lecture

Neural Transduction for Multilingual Lexical Translation

Downloads