5 papers
Automatically Selecting Useful Phrases for Dialogue Act Tagging
Ken Samuel, Sandra Carberry, K. Vijay-Shanker
We present an empirical investigation of various ways to automatically identify phrases in a tagged corpus that are useful for dialogue act tagging. We found that a new method (whi…
An Investigation of Transformation-Based Learning in Discourse
Ken Samuel, Sandra Carberry, K. Vijay-Shanker
This paper presents results from the first attempt to apply Transformation-Based Learning to a discourse-level Natural Language Processing task. To address two limitations of the s…
Dialogue Act Tagging with Transformation-Based Learning
Ken Samuel, Sandra Carberry, K. Vijay-Shanker
For the task of recognizing dialogue acts, we are applying the Transformation-Based Learning (TBL) machine learning algorithm. To circumvent a sparse data problem, we extract value…
Computing Dialogue Acts from Features with Transformation-Based Learning
Ken Samuel, Sandra Carberry, K. Vijay-Shanker
To interpret natural language at the discourse level, it is very useful to accurately recognize dialogue acts, such as SUGGEST, in identifying speaker intentions. Our research expl…
Integrating Text Plans for Conciseness and Coherence
Terrence Harvey, Sandra Carberry
Our experience with a critiquing system shows that when the system detects problems with the user's performance, multiple critiques are often produced. Analysis of a corpus of actu…