Dunker, PeterPaduschek, RonnyDittmar, ChristianNowak, StefanieGruhne, Matthias2017-11-142017-11-1420099-78300-278587https://dl.gi.de/handle/20.500.12116/4982This paper describes a technical solution for automated semantic indexing of music and images for a media archive environment. The indexing is based on a multi-modal low-level feature extraction and semantic high-level feature classification such as mood, genre, daytime or visual scene types. The classification on both, the audio and the visual information is based on a generic machine learning core architecture. A combination and cleansing process validates for improving the classification results. This paper presents the technical realization of a prototype and its corresponding evaluation. Finally, the practical relevance of this technology results, based on the findings of the evaluation is discussed.enmulti-modal media indexingmedia archives indexingmusic retrievalimage retrievalText/Conference Paper0947-5125