@inproceedings{61287f5404664811a28b49f618403aec,
title = "Combined supervised and unsupervised approaches for automatic segmentation of radiophonic audio streams",
abstract = "Speech/music discrimination is one of the most studied topics in the domain of audio data segmentation. In this paper, we propose and evaluate a novel method that includes feature selection and a combined supervised and unsupervised strategy for audio streams segmentation. A number of alternatives solutions for each component are assessed, and the optimized system is compared to the approaches proposed in the framework of the ESTER campaign.",
keywords = "Audio segmentation, Novelty detection, Speech/music discrimination",
author = "Ga{\"e}l Richard and Mathieu Ramona and Slim Essid",
year = "2007",
month = aug,
day = "6",
doi = "10.1109/ICASSP.2007.366272",
language = "English",
isbn = "1424407281",
series = "ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings",
pages = "II461--II464",
booktitle = "2007 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '07",
note = "2007 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '07 ; Conference date: 15-04-2007 Through 20-04-2007",
}