Analysis of the Data Quality of Audio Features of Environmental Sounds
Dalibor Mitrovic (Vienna University of Technology, Austria)
Matthias Zeppelzauer (Vienna University of Technology, Austria)
Horst Eidenberger (Vienna University of Technology, Austria)
Abstract: In this paper we perform statistical data analysis of a broad set of state-of-the-art audio features and low-level MPEG-7 audio descriptors. The investigation comprises data analysis to reveal redundancies between state-of-the-art audio features and MPEG-7 audio descriptors. We introduce a novel measure to evaluate the information content of a descriptor in terms of variance. Statistical data analysis reveals the amount of variance contained in a feature. It enables identification of independent and redundant features. This approach assists in efficient selection of orthogonal features for content-based retrieval. We believe that a good feature should provide descriptions with high variance for the underlying data. Combinations of features should consist of decorrelated features in order to increase expressiveness of the descriptions. Although MPEG-7 is a popular and widely used standard for multimedia description, only few investigations do exist that address analysis of the data quality of low-level MPEG-7 descriptions.
Keywords: content-based multimedia retrieval, feature analysis, feature extraction, low-level MPEG-7 audiodescriptors, statistical data analysis
Categories: G.3, H.3.1, H.3.3