Abstract
This paper presents our recent research work on applying probabilistic generative models to Mandarin Chinese broadcast news retrieval and summarization. Most models can be trained in either a supervised or unsupervised manner. In addition, both literal term matching and concept matching strategies have been intensively investigated. This paper also presents a prototype web-based Mandarin Chinese broadcast news retrieval system, which is based on technologies such as automatic story segmentation, automatic speech recognition, spoken document retrieval and summarization.
| Original language | English |
|---|---|
| Pages | 331-337 |
| Number of pages | 7 |
| Publication status | Published - 2009 |
| Event | Asia-Pacific Signal and Information Processing Association 2009 Annual Summit and Conference, APSIPA ASC 2009 - Sapporo, Japan Duration: 2009 Oct 4 → 2009 Oct 7 |
Other
| Other | Asia-Pacific Signal and Information Processing Association 2009 Annual Summit and Conference, APSIPA ASC 2009 |
|---|---|
| Country/Territory | Japan |
| City | Sapporo |
| Period | 2009/10/04 → 2009/10/07 |
ASJC Scopus subject areas
- Computer Networks and Communications
- Information Systems
- Electrical and Electronic Engineering
- Communication