Work

Story segmentation of brodcast news in English, Mandarin and Arabic

Year: 2006

Type: conference-paper

Abstract: In this paper, we present results from a Broadcast News story segmentation system developed for the SRI NIGHTINGALE system operating on English, Arabic and Mandarin news shows to provide input to subsequent question-answering processes. Using a rule-induction algorithm with automatically extracted acoustic and lexical features, we report success rates that are competitive with state-of-the-art systems on each input language. We further demonstrate that features useful for English and Mandarin are not discriminative for Arabic.

Source: Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT)

DOI: 10.3115/1614049.1614081

Authors: Andrew Rosenberg, Julia Hirschberg

Institution: Columbia University

Language: English

Topic: Speech Recognition and Synthesis

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: bronze

Funders: Defense Advanced Research Projects Agency, Advanced Research Projects Agency

Award: G3190074090