Name
Abstract | ||
|---|---|---|
This paper presents an analysis of named entity recognition and classification in spontaneous speech transcripts. We annotated a significant fraction of the Switchboard corpus with six named entity classes and investigated a battery of machine learning models that include lexical, syntactic, and semantic attributes. The best recognition and classification model obtains promis- ing results, approaching within 5% a system evaluated on clean textual data. |
Year | Venue | Keywords |
|---|---|---|
2005 | INTERSPEECH | machine learning |
Field | DocType | Citations |
Entity linking,Computer science,Speech recognition,Named-entity recognition | Conference | 18 |
PageRank | References | Authors |
1.36 | 2 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mihai Surdeanu | 1 | 2582 | 174.69 |
| Jordi Turmo | 2 | 306 | 30.52 |
| Eli Comelles | 3 | 18 | 1.36 |