Name
Abstract | ||
|---|---|---|
We describe a probabilistic reference disambiguation mechanism developed for a spoken dialogue system mounted on an autonomous robotic agent. Our mechanism performs probabilistic comparisons between features specified in referring expressions (e.g. size and colour) and features of objects in the domain. The results of these comparisons are combined using a function weighted on the basis of the specified features. Our evaluation shows high reference resolution accuracy across a range of spoken referring expressions. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1007/978-3-540-89378-3_16 | Australasian Conference on Artificial Intelligence |
Keywords | Field | DocType |
probabilistic reference disambiguation mechanism,high reference resolution accuracy,understand spoken descriptions,dialogue system,autonomous robotic agent,probabilistic comparison,probabilistic feature,specified feature | Parse tree,Expression (mathematics),Computer science,Lexical item,Speech recognition,Feature matching,Artificial intelligence,Natural language processing,Probabilistic logic | Conference |
Volume | ISSN | Citations |
5360 | 0302-9743 | 2 |
PageRank | References | Authors |
0.46 | 12 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ingrid Zukerman | 1 | 994 | 113.39 |
| Enes Makalic | 2 | 55 | 11.54 |
| Michael Niemann | 3 | 22 | 3.22 |