Recently, audio segmentation has attracted research interest because of its usefulness in several applications like\r\naudio indexing and retrieval, subtitling, monitoring of acoustic scenes, etc. Moreover, a previous audio\r\nsegmentation stage may be useful to improve the robustness of speech technologies like automatic speech\r\nrecognition and speaker diarization. In this article, we present the evaluation of broadcast news audio\r\nsegmentation systems carried out in the context of the AlbayzÃ?Ân-2010 evaluation campaign. That evaluation\r\nconsisted of segmenting audio from the 3/24 Catalan TV channel into five acoustic classes: music, speech, speech\r\nover music, speech over noise, and the other. The evaluation results displayed the difficulty of this segmentation\r\ntask. In this article, after presenting the database and metric, as well as the feature extraction methods and\r\nsegmentation techniques used by the submitted systems, the experimental results are analyzed and compared,\r\nwith the aim of gaining an insight into the proposed solutions, and looking for directions which are promising.
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