In addition to information, text contains attitudinal, and more specifically, emotional content.
This paper explores the text-based emotion prediction problem empirically, using …

We explored the reliability of detecting a learner's affect from conversational features
extracted from interactions with AutoTutor, an intelligent tutoring system (ITS) that helps …

As technology and human-computer interaction advances, there is an increased interest in
affective computing. One of the current challenges in computational speech and text …

In recent years, prompting has quickly become one of the standard ways of steering the
outputs of generative machine learning models, due to its intuitive use of natural language …

During the past years the “mystery” of emotions has increasingly attracted interest in
research on human–computer interaction. In this work we investigate the problem of how to …

Emotion Classification is the task of automatically associating a text with a human emotion.
State-of-the-art models are usually learned using annotated corpora or rely on hand-crafted …

The generation of synthetic speech with a certain degree of expressiveness has been
successful for some particular applications or speaking styles (eg emotions). In this context …

Generating emotions in speech is currently a hot topic of research given the requirement of
modern human-machine interaction systems to produce expressive speech. We present the …

A method for speech expressiveness change detection is presented which combines a
dimensional analysis of speech expression, a Principal Component Analysis technique, as …

Storytelling speech entails a particular speaking style that contains subtle expressive
nuances represented by specific acoustic cues. In the literature, different pieces of research …