Semantic Segmentation of Radio Programs Using Social Network Analysis and Duration Distribution Modeling
| Type of publication: | Conference paper |
| Citation: | vinciarelli:icmevincia:2007 |
| Booktitle: | IEEE International Conference on Multimedia and Expo (ICME) |
| Year: | 2007 |
| Note: | IDIAP-RR 06-75 |
| Crossref: | vinciarelli:rr06-75: |
| Abstract: | This work presents and compare two approaches for the semantic segmentation of broadcast news: the first is based on Social Network Analysis, the second is based on Poisson Stochastic Processes. The experiments are performed over 27 hours of material: preliminary results are obtained by addressing the problem of splitting different episodes of the same program into two parts corresponding to a news bulletin and a talk-show respectively. The results show that the transition point between the two parts can be detected with an average error of around three minutes, i.e. roughly 5 percent of each episode duration. |
| Userfields: | ipdmembership={vision}, |
| Keywords: | |
| Projects: |
Idiap |
| Authors: | |
| Added by: | [UNK] |
| Total mark: | 0 |
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