Name
Abstract | ||
|---|---|---|
Automatically detecting dialogue structure within corpora of human-human dialogue is the subject of increasing attention. In the domain of tutorial dialogue, automatic discovery of dialogue structure is of particular interest because these structures inherently represent tutorial strategies or modes, the study of which is key to the design of intelligent tutoring systems that communicate with learners through natural language. We propose a methodology in which a corpus of human-human tutorial dialogue is first manually annotated with dialogue acts. Dependent adjacency pairs of these acts are then identified through X2 analysis, and hidden Markov modeling is applied to the observed sequences to induce a descriptive model of the dialogue structure. |
Year | Venue | Keywords |
|---|---|---|
2009 | HLT-NAACL (Short Papers) | automatic discovery,dialogue structure,hidden markov model,adjacency pair analysis,dialogue act,human-human dialogue,dependent adjacency pair,descriptive model,x2 analysis,tutorial dialogue,tutorial strategy,human-human tutorial dialogue |
Field | DocType | Citations |
Computer science,Dialogue acts,Natural language,Artificial intelligence,Natural language processing,Hidden Markov model,Adjacency pairs,Machine learning | Conference | 13 |
PageRank | References | Authors |
0.72 | 8 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Kristy Elizabeth Boyer | 1 | 540 | 64.01 |
| Robert Phillips | 2 | 168 | 13.02 |
| Eun Young Ha | 3 | 135 | 8.37 |
| Michael D. Wallis | 4 | 129 | 9.12 |
| Mladen A. Vouk | 5 | 452 | 49.92 |
| James C. Lester | 6 | 2398 | 282.35 |