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Audio segmentation of broadcast news : a hierarchical system with feature selection for the Albayzin-2010 evaluation

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10.1109/ICASSP.2011.5946414
 
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Butko, Taras
Nadeu Camprubí, ClimentMés informacióMés informacióMés informació
Document typeConference lecture
Defense date2011
PublisherIEEE Press. Institute of Electrical and Electronics Engineers
Rights accessRestricted access - publisher's policy
All rights reserved. This work is protected by the corresponding intellectual and industrial property rights. Without prejudice to any existing legal exemptions, reproduction, distribution, public communication or transformation of this work are prohibited without permission of the copyright holder
Abstract
In this paper, we present an audio segmentation system for broadcast news, and its results in the Albayzin-2010 evaluation. First of all, the Albayzin-2010 evaluation setup, developed by the authors, is presented; in particular, the database and the metric are described. The reported hierarchical HMM-GMM-based system is composed of one binary detector for each of the five considered classes (music, speech, speech over music, speech over noise and other). A fast one-pass-training feature selection technique is adapted to the audio segmentation task to improve the results and to reduce the dimensionality of the input feature vector.
CitationButko, T.; Nadeu, C. Audio segmentation of broadcast news : a hierarchical system with feature selection for the Albayzin-2010 evaluation. A: International Conference on Acoustics, Speech and Signal Processing. "2011 IEEE International Conference on Acoustics, Speech, and Signal Processing Proceedings". Barcelona: IEEE Press. Institute of Electrical and Electronics Engineers, 2011, p. 357-360. 
URIhttp://hdl.handle.net/2117/15469
DOI10.1109/ICASSP.2011.5946414
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