162512 20251017144631.0 doi 10.1109/ICASSP.2013.6637755 sideral 84546 ART-2013-84546 eng Castan, D. Universidad de Zaragoza Segmentation-by-classification system based on factor analysis 2013 This paper proposes a novel audio segmentation-by-classification system based on Factor Analysis (FA) with a channel compensation matrix for each class and scoring the fixed-length segments as the log-likelihood ratio between class/no-class. The scores are smoothed and the most probable sequence is computed with a Viterbi algorithm. The system described here is designed to segment and classify the audio files coming from broadcast programs into five different classes: speech (SP), speech with noise (SN), speech with music (SM), music (MU) or others (OT). This task was proposed in the Albayzin 2010 evaluation campaign. The system is compared with the winning system of the evaluation achieving lower error rate in SP and SN. These classes represent 3/4 of the total amount of the data. Therefore, the FA segmentation system gets a reduction in the average segmentation error rate. info:eu-repo/grantAgreement/ES/MINECO/TIN2011-28169-C05-02 info:eu-repo/semantics/closedAccess All rights reserved http://www.europeana.eu/rights/rr-f/ info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Ortega, A. Universidad de Zaragoza (orcid)0000-0002-3886-7748 Villalba, J. (orcid)0000-0001-9459-8426 Miguel, A. Universidad de Zaragoza (orcid)0000-0001-5803-4316 Lleida, E. Universidad de Zaragoza (orcid)0000-0001-9137-4013 5008 800 Universidad de Zaragoza Dpto. Ingeniería Electrón.Com. Área Teoría Señal y Comunicac. 2013 (2013), 783-787 Proc. IEEE Int. Conf. Acoust. Speech Signal Process. Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing 1520-6149 221354 http://zaguan.unizar.es/record/162512/files/texto_completo.pdf Versión publicada 2882467 http://zaguan.unizar.es/record/162512/files/texto_completo.jpg?subformat=icon icon Versión publicada oai:zaguan.unizar.es:162512 articulos driver 2025-10-17-14:26:24 ARTICLE