DocumentCode :
2659906
Title :
Identifying salient utterances of online spoken documents using descriptive hypertext
Author :
Zhu, Xiaodan ; Kazemian, Siavash ; Penn, Gerald
Author_Institution :
Dept. of Comput. Sci., Univ. of Toronto, Toronto, ON
fYear :
2008
fDate :
15-19 Dec. 2008
Firstpage :
173
Lastpage :
176
Abstract :
The Internet has become an important supply channel of spoken documents. Efficient ways of navigating their content are highly desirable. This paper aims to identify the most salient utterances from online spoken documents using relevant hypertext that encapsulates key information. Experimental results show that hypertext features are helpful when properly utilized and if the bit rates used to compress the spoken documents are reasonable.
Keywords :
Internet; data compression; data encapsulation; document handling; speech coding; Internet; descriptive hypertext; key information encapsulation; online spoken documents; salient utterance identification; spoken document compression; Cellular neural networks; Data mining; Information retrieval; Internet; Lattices; Navigation; Redundancy; Speech recognition; Support vector machine classification; Support vector machines; Speech summarization; sentence extraction; web document summarization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Spoken Language Technology Workshop, 2008. SLT 2008. IEEE
Conference_Location :
Goa
Print_ISBN :
978-1-4244-3471-8
Electronic_ISBN :
978-1-4244-3472-5
Type :
conf
DOI :
10.1109/SLT.2008.4777868
Filename :
4777868
Link To Document :
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