Alessandro Valitutti

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Affective computing is advancing as a field that allows a new form of human computer interaction, in addition to the use of natural language. There is a wide perception that the future of human-computer interaction is in themes such as entertainment, emotions, aesthetic pleasure, motivation, attention, engagement, etc. Studying the relation between natural(More)
In this paper we present an evaluation of new techniques for automatically detecting emotions in text. The study estimates categorical model and dimensional model for the recognition of four affective states: Anger, Fear, Joy, and Sadness that are common emotions in three datasets: SemEval-2007 " Affective Text " , ISEAR (International Survey on Emotion(More)
We employ a corpus-based approach to generate content and form in poetry. The main idea is to use two different corpora, on one hand, to provide semantic content for new poems, and on the other hand, to generate a specific grammatical and poetic structure. The approach uses text mining methods, morphological analysis, and morphological synthesis to produce(More)
A fluent ability to associate tasks, concepts, ideas, knowledge and experiences in a relevant way is often considered an important factor of creativity, especially in problem solving. We are interested in providing computational support for discovering such creative associations. In this paper we design minimally supervised methods that can perform well in(More)
We propose a method for automated generation of adult humor by lexical replacement and present empirical evaluation results of the obtained humor. We propose three types of lexical constraints as building blocks of humorous word substitution: constraints concerning the similarity of sounds or spellings of the original word and the substitute, a constraint(More)
This paper presents resources and functionalities for the selection of affective evaluative terms. An affective hierarchy as an extension of the WordNet-Affect lexical database was developed in the first place. The second phase was the development of a semantic similarity function, acquired automatically in an unsupervised way from a large corpus of texts(More)
We address the challenging task of automatically composing lyrical songs with matching musical and lyrical features, and we present the first prototype, M.U. Sicus-Apparatus, to accomplish the task. The focus of this paper is especially on generation of art songs (lieds). The proposed approach writes lyrics first and then composes music to match the lyrics.(More)