Creativity and artificial intelligence
Artificial Intelligence - Special issue: artificial intelligence 40 years later
ECCBR '02 Proceedings of the 6th European Conference on Advances in Case-Based Reasoning
Lexical cohesion computed by thesaural relations as an indicator of the structure of text
Computational Linguistics
WordNet::Similarity: measuring the relatedness of concepts
HLT-NAACL--Demonstrations '04 Demonstration Papers at HLT-NAACL 2004
Computational creativity tools for songwriters
CALC '10 Proceedings of the NAACL HLT 2010 Second Workshop on Computational Approaches to Linguistic Creativity
Automatic analysis of rhythmic poetry with applications to generation and translation
EMNLP '10 Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing
Unsupervised discovery of rhyme schemes
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies: short papers - Volume 2
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
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Word associations are an important element of linguistic creativity. Traditional lexical knowledge bases such as WordNet formalize a limited set of systematic relations among words, such as synonymy, polysemy and hypernymy. Such relations maintain their systematicity when composed into lexical chains. We claim that such relations cannot explain the type of lexical associations common in poetic text. We explore in this paper the usage of Word Association Norms (WANs) as an alternative lexical knowledge source to analyze linguistic computational creativity. We specifically investigate the Haiku poetic genre, which is characterized by heavy reliance on lexical associations. We first compare the density of WAN-based word associations in a corpus of English Haiku poems to that of WordNet-based associations as well as in other non-poetic genres. These experiments confirm our hypothesis that the non-systematic lexical associations captured in WANs play an important role in poetic text. We then present Gaiku, a system to automatically generate Haikus from a seed word and using WAN-associations. Human evaluation indicate that generated Haikus are of lesser quality than human Haikus, but a high proportion of generated Haikus can confuse human readers, and a few of them trigger intriguing reactions.