Audio segmentation of broadcast news : a hierarchical system with feature selection for the Albayzin-2010 evaluation
Document typeConference lecture
PublisherIEEE Press. Institute of Electrical and Electronics Engineers
Rights accessRestricted access - publisher's policy
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.