Name
Abstract | ||
|---|---|---|
We present a topic boundary detection method that searches for connections between sequences of utterances in multi party dialogues. The connections are established based on word identity. We compare our method to a state-of-the art automatic topic boundary detection method that was also used on multi party dialogues. We checked various methods of preprocessing of the data, including stemming, lemmatization and stopword filtering with a text-based as we ll as speech-based stopword lists. Using standard evaluati on methods we found that our method outperformed the state-of-the art method. |
Year | Venue | Field |
|---|---|---|
2008 | LREC | Lemmatisation,Computer science,Filter (signal processing),Speech recognition,Preprocessor,Boundary detection,Natural language processing,Artificial intelligence |
DocType | Citations | PageRank |
Conference | 0 | 0.34 |
References | Authors | |
19 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Margot Mieskes | 1 | 2 | 0.95 |
| Michael Strube | 2 | 21 | 4.13 |