Name
Abstract | ||
|---|---|---|
For complex natural language understanding systems with a large number of statistically confusable but semantically different for- mal commands, there are many difficulties in performing an accu- rate translation of a user input into a formal command in a single step. This paper addresses scalability issues in natural language understanding, and describes a method for performing the transla- tion in a hierarchical manner. The hierarchical method improves the system accuracy, reduces the computational complexity of the translation, provides additional numerical robustness during train- ing and decoding, and permits a more efficient packaging of the components of the natural language understanding system. |
Year | Venue | Keywords |
|---|---|---|
2000 | INTERSPEECH | computational complexity |
Field | DocType | Citations |
Question answering,Temporal annotation,Computer science,Natural language understanding,Universal Networking Language,Artificial intelligence,Natural language processing,Feature based,Scalability | Conference | 5 |
PageRank | References | Authors |
1.48 | 9 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ganesh N. Ramaswamy | 1 | 213 | 25.72 |
| Jan Kleindienst | 2 | 220 | 23.74 |