| Paper: | AE-L1.3 | ||
| Session: | Audio Structure, Similarity and Segmentation | ||
| Time: | Tuesday, May 16, 11:10 - 11:30 | ||
| Presentation: | Lecture | ||
| Topic: | Audio and Electroacoustics: Applications to Music | ||
| Title: | Enhancing Similarity Matrices for Music Audio Analysis | ||
| Authors: | Meinard Mueller, Frank Kurth, University of Bonn, Germany | ||
| Abstract: | Similarity matrices have become an important tool in music audio analysis. However, the quadratic time and space complexity as well as the intricacy of extracting the desired structural information from these matrices are often prohibitive with regard to real-world applications. In this paper, we describe an approach for enhancing the structural properties of similarity matrices based on two concepts: first, we introduce a new class of robust and scalable audio features allowing to absorb local temporal variations. As a second contribution, we then incorporate contextual information into the local similarity measure. The resulting enhancement not only allows to significantly reduce the matrix size but also to ease the structure extraction step. As an example, we sketch the application of our techniques to the problems of audio summarization and audio synchronization, obtaining effective and computationally feasible algorithms. | ||
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