Name
Abstract | ||
|---|---|---|
Speaker clustering aims to automatically cluster speech segments for each speaker. By speaker clustering, we can discover main cast list from long videos and retrieve their relevant video clips for efficient browsing. In this paper, we propose a dialogue supervised speaker clustering method, which makes use of the visual dialogue analysis results to improve the performance of speaker clustering. Compared with the traditional approach based only on acoustic features, the dialogue supervised speaker clustering approach can get significant improvement on the clustering result for movie and TV series. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1007/978-3-540-89796-5_71 | PCM |
Keywords | Field | DocType |
traditional approach,dialogue supervised speaker,tv series,speaker clustering,long video,efficient browsing,visual dialogue analysis result,cluster speech segment,acoustic feature,visual dialogue analysis,clustering result,speech segmentation | Pattern recognition,Computer science,Speech recognition,Speaker recognition,Speaker diarisation,Natural language processing,Artificial intelligence,Conceptual clustering,Cluster analysis,Speech segmentation,Brown clustering | Conference |
Volume | ISSN | Citations |
5353 | 0302-9743 | 1 |
PageRank | References | Authors |
0.35 | 7 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Shuang Zhang | 1 | 6 | 0.83 |
| Wei Hu | 2 | 182 | 14.17 |
| Tao Wang | 3 | 238 | 23.70 |
| Jia Liu | 4 | 183 | 32.42 |
| Yimin Zhang | 5 | 359 | 28.66 |