Paper: Emotions From Text: Machine Learning For Text-Based Emotion Prediction

ACL ID H05-1073
Title Emotions From Text: Machine Learning For Text-Based Emotion Prediction
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2005
Authors

In addition to information, text con- tains attitudinal, and more specifically, emotional content. This paper explores the text-based emotion prediction prob- lem empirically, using supervised machine learning with the SNoW learning archi- tecture. The goal is to classify the emo- tional affinity of sentences in the narra- tive domain of children’s fairy tales, for subsequent usage in appropriate expres- sive rendering of text-to-speech synthe- sis. Initial experiments on a preliminary data set of 22 fairy tales show encourag- ing results over a na¨ıve baseline and BOW approach for classification of emotional versus non-emotional contents, with some dependency on parameter tuning. We also discuss results for a tripartite model which covers emotional valence, as well as feature set alte...