Name
Abstract | ||
|---|---|---|
In this paper we describe a framework for stylistic control of the generation process. The approach correlates stylistic dimensions obtained from a corpus-based factor analysis with internal generator decisions, and uses the correlation to direct the generator towards particular style settings. We illustrate this approach with a prototype generator of medical information. We compare our framework with previous approaches according to how they define, characterise and specify style and how effective they axe at controlling it, arguing that our framework offers a generic, practical, evaluable approach to the problem of stylistic control. |
Year | DOI | Venue |
|---|---|---|
2004 | 10.1007/978-3-540-27823-8_13 | LECTURE NOTES IN ARTIFICIAL INTELLIGENCE |
Keywords | Field | DocType |
factor analysis | Natural language generation,Decision analysis,Argument,Computer science,Natural language,Natural language processing,Artificial intelligence,Process control | Conference |
Volume | ISSN | Citations |
3123 | 0302-9743 | 9 |
PageRank | References | Authors |
0.80 | 3 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Daniel S. Paiva | 1 | 37 | 2.95 |
| Roger Evans | 2 | 344 | 55.12 |