Name
Abstract | ||
|---|---|---|
This paper describes an implementation of a shell-like programming interface that utilizes referential context (that is, information about the current state of an interfaced application) in order to achieve accurate recognition -- even in user-defined domains with no available domain-specific training corpora. The interface incorporates a knowledge of context into its model of syntax, yielding a referential semantic language model. Interestingly, the referential semantic language model exploits context dynamically, unlike other recent systems, by using incremental processing and the limited stack memory of an HMM-like time series model. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1145/1378773.1378811 | IUI |
Keywords | Field | DocType |
hmm-like time series model,language interface,interfaced application,shell-like programming interface,referential context,context dynamically,accurate recognition,available domain-specific training corpus,incremental processing,referential semantic language model,data-poor domain,current state,time series model,language model | Time series,Computer science,Speech recognition,Exploit,Artificial intelligence,Natural language processing,Syntax,Language model,Speech summarization,Spoken language,Stack-based memory allocation | Conference |
Citations | PageRank | References |
1 | 0.37 | 14 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Stephen Wu | 1 | 147 | 11.73 |
| Lane Schwartz | 2 | 209 | 18.01 |
| William Schuler | 3 | 125 | 17.78 |