Please use this identifier to cite or link to this item: http://hdl.handle.net/10071/27931
Author(s): Marujo, L.
Ribeiro, R.
Matos, D. M. de.
Neto, J. P.
Gershman, A.
Carbonell, J.
Editor: Sojka, P., Horák, A., Kopeček, I., and Pala, K.
Date: 2012
Title: Key phrase extraction of lightly filtered broadcast news
Volume: 7499
Book title/volume: Text, Speech and Dialogue. TSD 2012. Lecture Notes in Computer Science
Pages: 290 - 297
Event title: 15th International Conference on Text, Speech and Dialogue, TSD 2012
Reference: Marujo, L., Ribeiro, R., Matos, D. M. de., Neto, J. P., Gershman, A., & Carbonell, J. (2012). Key phrase extraction of lightly filtered broadcast news. In P. Sojka, A. Horák, I. Kopeček, & K. Pala (Eds.) Text, Speech and Dialogue. TSD 2012. Lecture Notes in Computer Science (vol 7499, pp. 290-297). Springer. https://doi.org/10.1007/978-3-642-32790-2_35
ISSN: 0302-9743
ISBN: 978-3-642-32790-2
DOI (Digital Object Identifier): 10.1007/978-3-642-32790-2_35
Keywords: Keyphrase extraction
Speech summarization
Speech browsing
Broadcast news speech recognition
Abstract: This paper explores the impact of light filtering on automatic key phrase extraction (AKE) applied to Broadcast News (BN). Key phrases are words and expressions that best characterize the content of a document. Key phrases are often used to index the document or as features in further processing. This makes improvements in AKE accuracy particularly important. We hypothesized that filtering out marginally relevant sentences from a document would improve AKE accuracy. Our experiments confirmed this hypothesis. Elimination of as little as 10% of the document sentences lead to a 2% improvement in AKE precision and recall. AKE is built over MAUI toolkit that follows a supervised learning approach. We trained and tested our AKE method on a gold standard made of 8 BN programs containing 110 manually annotated news stories. The experiments were conducted within a Multimedia Monitoring Solution (MMS) system for TV and radio news/programs, running daily, and monitoring 12 TV and 4 radio channels.
Peerreviewed: yes
Access type: Open Access
Appears in Collections:IT-CRI - Comunicações a conferências internacionais

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