Abstract Deep Neural Networks (DNNs) have shown to outperform traditional methods in
various visual recognition tasks including Facial Expression Recognition (FER). In spite of …

We propose a first-ever attempt to employ a Long Short-Term memory based framework to
predict humor in dialogues. We analyze data from a popular TV-sitcom, whose canned …

Irony and humour are just two of many forms of figurative language. Approaches to identify
in vast volumes of data such as the internet humorous or ironic statements is important not …

Since the late 1990s when speech companies began providing their customer-service
software in the market, people have gotten used to speaking to machines. As people interact …

Fake news can be disseminated on social media platforms due to users' inability to
distinguish it from true news as well as the nature of heuristic-driven online sharing. We use …

A conversational agent, capable to have a ldquosense of humourrdquo is presented. The
agent can both generate humorous sentences and recognize humoristic expressions …

The widespread use of bots to support software development makes social coding platforms
such as GitHub a particularly rich source of data for the study of human-bot interaction …

This work presents a first step to a general implementation of the Semantic-Script Theory of
Humor (SSTH). Of the scarce amount of research in computational humor, no research had …

In this paper, we outline an approach of end-to-end interactive systems with emotional
embeddings, which are transfered from a large corpus. We show how to apply emotional …

We consider automated generation of humorous texts by substitution of a single word in a
given short text. In this setting, several factors that potentially contribute to the funniness of …