Portugal

Natural language generation provides designers with methods for automatically generating text, e.g. for creating summaries, chatbots and game content. In practise, text generators are often either learned and hard to interpret, or created by hand using techniques such as grammars and templates. In this paper, we introduce a novel grammar induction algorithm for learning interpretable grammars for generative purposes, called GITTA. We also introduce the novel notion of template trees to discover latent templates in corpora to derive these generative grammars. By using existing human-created grammars, we found that the algorithm can reasonably approximate these grammars using only a few examples. These results indicate that GITTA could be used to automatically learn interpretable and easily modifiable grammars, and thus provide a stepping stone for human-machine co-creation of generative models.

ICCC&#39;20

Discovering Textual Structures: Generative Grammar Induction using Template Trees

tracery

generative grammar

grammar induction

machine learning

**BRACIS** originated from the combination of the two most important scientific events in Brazil in Artificial Intelligence (AI) and Computational Intelligence (CI): the Brazilian Symposium on Artificial Intelligence – **SBIA** (22 editions), and the Brazilian Symposium on Neural Networks – **SBRN** (13 editions). **ENIAC** is a national forum for researchers, practitioners, educators and students to present and discuss innovations, trends, experiences, developments and work in progress in the fields of Artificial and Computational Intelligence. **STIL** is the bi-annual Language Technology event.
All events are supported by the Brazilian Computer Society – Special Interest Groups: **CE-IA**, **CE-IC** and **CE-PLN**.

To access the 10th Brazilian Conference on Intelligent Systems (**BRACIS**), you need to register for the conference.  Please visit the Conference official site to register

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BRACIS 2021

BRACIS originated from the combination of the two most important scientific events in Brazil in Artificial Intelligence (AI) and Computational Intelligence (CI): the Brazilian Symposium on Artificial Intelligence – SBIA (22 editions), and the Brazilian Symposium on Neural Networks – SBRN (13 editions). 
ENIAC is a national forum for researchers, practitioners, educators and students to present and discuss innovations, trends, experiences, developments and work in progress in the fields of Artificial and Computational Intelligence. 
STIL is the bi-annual Language Technology event.
All events are supported by the Brazilian Computer Society – Special Interest Groups: CE-IA, CE-IC and CE-PLN

poster

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.



We introduce CANIS, our computationally creative system for generating novel constellations. We explain the motivations behind its creation, how it works, and demonstrate several of its artifacts. 

Creative Constellation Generation

"Humor is incorporated into our daily interactions, but conceiving jokes ideas can be inherently difficult to produce spontaneously. The PAUL BOT system, “puns are usually lame but occasionally terrific”, includes features of the JAPE system by incorporating aspects of the SAD generator, templates, and sentence forms to automatically generate a pun (Ritchie 2003). A two-word database is composed of adjective-noun phrases that contain a homophone. The punchline to the pun is replacing a word in the two- word phrase with a homophone. A synonym is derived from the homophone, and a hypernym is chosen from the non- homophone word in the original phrase. The synonym and the hypernym are incorporated into a predetermined sentence structure to construct the question. Surveys were conducted to evaluate our artifacts produced by PAUL BOT in order to identify future improvements of the system. The creativity in the system is attributed to the novelty of the unique artifacts, the level of surprise, the typicality of the artifacts as classic puns, and the intentionality by providing the connection between the setup and punchline. This paper proposes the PAUL BOT system that incorporates the JAPE system to create puns in order to produce a humorous, creative system utilized for entertainment.
Source: github.com/knw7x9/PunGenerator"

Computational Humor: Automated Pun Generation

"We present ERwEM (Events Represented with Emotive Music), a system that generates cross-domain artefacts between text and music by drawing from emotional sentiments. Our system uses keywords extracted from a
news article to filter live-stream tweets containing these keywords and analyze the tweet collection’s emotion data. It then uses the emotion sentiment (a scale from positive to negative) to influence the mood of the music it writes using an adapted bi-axial long short term memory (BALSTM) model. From this, our system determines
which mode the generated song will be transposed to. We use the FACE model to characterize the creative aspects of our system as a collection of generative acts. We provide examples of the artefacts our system generates as well as the response we received from external sources who reviewed the generated songs."

ERwEM: Events Represented with Emotive Music Using Topic-Filtered Tweets

"We propose three methods for the adaptation of well-known sayings~(e.g., proverbs, movie titles) for a context, given by a textual input~(e.g. news headline).
These methods -- word substitution, analogy and vector difference -- present different ways of exploiting word embeddings for word replacement towards a new text that should be semantically related to the input, in the sense that it could be used as a sub-title or comment, though more creative.
They were further combined with two selection methods, based on word overlap and on sentence embeddings, and used in the production of text in context with a small set of Portuguese headlines. To better understand how well our purpose was suit, results were manually assessed. All methods produced text with both syntax and relatedness to the input above average, contrasting the underachieving funniness scores."

Exploring Word Embeddings for Text Adaptation to a given Context

In this paper, we present a system that generates letterpress-inspired typographic posters from a user-given text. This system employs lexicon-based approaches not only to recognise emotions and sentiments but also the colours related to the content. Moreover, the system generates and evolves outputs employing an Evolutionary Computation approach. The generated outputs are evaluated according to their legibility, aesthetics and semantics, throughout a multi-criteria hardwired fitness function scheme. Also, this system enables its users to guide the generation process through the dynamic definition of several setting parameters.

Evolutionary Experiments in Typesetting of Letterpress-Inspired Posters

The Pokérator is a generator of Pokémon names and descriptions, based on user input. The names are generated by blending words based on syllables or characters according to a bigram language model. An accompanying description is generated by filling a template with ConceptNet answers. This sentence is then used as a prompt for text generation with the GPT-2 language model which was finetuned on Pokédex entries. The evaluation of the generated Pokémon names shows that the names are not realistic, but appreciated and creative.

Pokérator - Unveil your inner Pokémon

In this paper, we provide a philosophical account of the value of creative systems for individuals and society. We characterize creativity in very broad philosophical terms, encompassing natural, existential, and social creative processes, such as natural evolution and entrepreneurship, and explain why creativity understood in this way is instrumental for advancing human well-being in the long term. We then explain why current mainstream AI tends to be anti-creative, which means that there are moral costs of employing this type of AI in human endeavors, although computational systems that involve creativity are on the rise. In conclusion, there is an argument for ethics to be more hospitable to creativity-enabling AI, which can also be in a trade-off with other values promoted in AI ethics, such as its explainability and accuracy.

The societal and ethical relevance of computational creativity

Trust is often considered valuable in a broad range of relationships, from professional collaborations to personal partnerships. This article examines the possibility of trust in a robotic system. By posing the question “can a robot do a trust fall?”, an investigation on the issues embedded in designing trusting systems is presented, using methods and perspectives from philosophy and engineering. Posing such a question helps us understand the physicality and embodiment of trust, as well as the limits and resources of robotics. 

Can a Robot Do a Trust Fall? Absurdity as a Component of Human Intelligence and Embodiment

In this paper we present R-VAE, a system designed for the exploration of latent spaces of musical rhythms. Unlike most previous work in rhythm modeling, R-VAE can be trained with small datasets, enabling rapid customization and exploration by individual users. R-VAE employs a data representation that encodes simple and compound meter rhythms. To the best of our knowledge, this is the first time that a network architecture has been used to encode rhythms with these characteristics, which are common in some modern popular music genres.

Creating Latent Spaces for Modern Music Genre Rhythms Using Minimal Training Data

The task of translating text to images holds some valid creative potential and has been the subject of study in Computational Creativity. In this paper, we present preliminary work focused on emoji translation. The work-in-progress system is based on techniques of information retrieval. We compare the performance of our system with three deep learning approaches using a text-to-emoji task. The preliminary results suggest some advantages of using a knowledge-base as opposed to a purely data-driven approach. This paper aims to situate the research, underline its relevance and attract valuable feedback for future developments.

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