Salcedo Sanz, SanchoGallardo Antolín, AscensiónLeiva Murillo, José MiguelBousoño Calzón, Carlos2021-06-182021-06-182006-04Salcedo-Sanz, S., Gallardo-Antolin, A., Leiva-Murillo, J. & Bousono-Calzon, C. (2006). Offline speaker segmentation using genetic algorithms and mutual information. IEEE Transactions on Evolutionary Computation, 10(2), pp. 175–186.1089-778Xhttps://hdl.handle.net/10016/32890We present an evolutionary approach to speaker segmentation, an activity that is especially important prior to speaker recognition and audio content analysis tasks. Our approach consists of a genetic algorithm (GA), which encodes possible segmentations of an audio record, and a measure of mutual information between the audio data and possible segmentations, which is used as fitness function for the GA. We introduce a compact encoding of the problem into the GA which reduces the length of the GA individuals and improves the GA convergence properties. Our algorithm has been tested on the segmentation of real audio data, and its performance has been compared with several existing algorithms for speaker segmentation, obtaining very good results in all test problems.12eng© 2006, IEEEGenetic Algorithms (GAs)Mutual informationSpeaker segmentationUnsupervised learningresearch articleTelecomunicacioneshttps://doi.org/10.1109/TEVC.2005.857079open access1752186IEEE Transactions on Evolutionary Computation10AR/0000001065