NDLI: A segmentation method of news video stories based on announcer’s voiceprint

Content Provider	IEEE Xplore Digital Library
Author	Xin-Wen Xu Guo-Hui Li Jian Yuan
Copyright Year	2008
Description	Author affiliation: Dept. of Syst. Eng., Nat. Univ. of Defense Technol., Changsha (Xin-Wen Xu; Guo-Hui Li; Jian Yuan)
Abstract	As an important step of content based news video retrieving and intelligence mining, semantic unit segmentation has attracted many researcherspsila interests. This paper focuses on a new method of news video stories segmentation which is based on the announcerspsila voiceprints. Firstly, the voiceprints included acoustic perception characteristics of all announcers have been extracted, and its Gaussian mixture model will be trained, then the audio clips included announcers and not announcers will be detected by the KL divergence method, at last the semantic units will be segmented under the guidance of video topic caption frames events and special structure knowledge of news program. Finally the 92.58% recall and the 96.02% precision have been achieved during more than 2 hourspsila experiment.
Starting Page	2749
Ending Page	2753
File Size	350650
Page Count	5
File Format	PDF
ISBN	9781424420957
DOI	10.1109/ICMLC.2008.4620874
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-07-12
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Feature extraction Speech Hidden Markov models Mel frequency cepstral coefficient Training Machine learning Cybernetics News video Voiceprint Story unit segmentation Gaussian mixture model
Content Type	Text
Resource Type	Article

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