This paper considers extractive summarization of Chinese spoken documents. In contrast to conventional approaches, we attempt to deal with the extractive summarization problem und...
Rapidly increasing quantities of multimedia and spoken content today demand fast and accurate retrieval approaches for convenient browsing. The spoken documents with wide variety ...
The Dublin City University participation in the CLEF 2006 CL-SR task concentrated on exploring the combination of the multiple fields associated with the documents. This was based...
Gareth J. F. Jones, Ke Zhang, Adenike M. Lam-Adesi...
The problem of joint modeling the text and image components of multimedia documents is studied. The text component is represented as a sample from a hidden topic model, learned wi...
Nikhil Rasiwasia, Jose Costa Pereira, Emanuele Cov...
There is considerable interest in interdisciplinary combinations of automatic speech recognition (ASR), machine learning, natural language processing, text classification and info...
Mark Dredze, Aren Jansen, Glen Coppersmith, Ken Wa...