Matemaattisen morfologian käyttö geometrisessa musiikinhaussa

The usual task in music information retrieval (MIR) is to find occurrences of a monophonic query pattern within a music database, which can contain both monophonic and polyphonic content. The so-called query-by-humming systems are a famous instance of content-based MIR. In such a system, the user's hummed query is converted into symbolic form to perform search operations in a similarly encoded database. The symbolic representation (e.g., textual, MIDI or vector data) is typically a quantized and simplified version of the sampled audio data, yielding to faster search algorithms and space requirements that can be met in real-life situations. In this thesis, we investigate geometric approaches to MIR. We first study some musicological properties often needed in MIR algorithms, and then give a literature review on traditional (e.g., string-matching-based) MIR algorithms and novel techniques based on geometry. We also introduce some concepts from digital image processing, namely the mathematical morphology, which we will use to develop and implement four algorithms for geometric music retrieval. The symbolic representation in the case of our algorithms is a binary 2-D image. We use various morphological pre- and post-processing operations on the query and the database images to perform template matching / pattern recognition for the images. The algorithms are basically extensions to classic image correlation and hit-or-miss transformation techniques used widely in template matching applications. They aim to be a future extension to the retrieval engine of C-BRAHMS, which is a research project of the Department of Computer Science at University of Helsinki

Rhythmic analysis of motion signals for music retrieval

viii, 108 leaves : ill. (chiefly col.) ; 29 cm.Includes abstract and appendix.Includes bibliographical references (leaves 100-108).This thesis presents a framework that queries a music database with rhythmic motion signals. Rather than the existing method to extract the motion signal's underlying rhythm by marking salient frames, this thesis proposes a novel approach, which converts the rhythmic motion signal to MIDI-format music and extracts its beat sequence as the rhythmic information of that motion. We extract "motion events" from the motion data based on characteristics such as movement directional change, root-y coordinate and angular-velocity. Those events are converted to music notes in order to generate an audio representation of the motion. Both this motion-generated music and the existing audio library are analyzed by a beat tracking algorithm. The music retrieval is completed based on the extracted beat sequences. We tried three approaches to retrieve music using motion queries, which are a mutual-information-based approach, two sample KS test and a rhythmic comparison algorithm. Feasibility of the framework is evaluated with pre-recorded music and motion recordings