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An algorithm for analyzing the rhythmic content of acoustic signals of polyphonic and multitimbral Western music is presented. The analysis consists of detecting sound onsets, computing an inter-onset interval (IOI) histogram, and estimating the duration of the shortest notes, i.e., the tatum period from the histogram. Robustness against tempo changes has(More)
In this paper, a system is described for the recognition of mixtures of noise sources in acoustic input signals. The problem is approached by utilizing both bottom-up signal analysis and top-down predictions of higher-level models. The developments are made using musical signals as test material. Validation experiments are presented both for self-generated(More)
Mobile music consumption is increasing and many of the current mobile phones already offer music listening capabilities. Still, most of the current automatic playlist generation systems do not function in the mobile domain. This paper presents an evaluation of a content-based prototype mobile playlist generator. A user study was conducted to find out the(More)
An automatic music transcription system is described which is applicable to the analysis of real-world musical recordings. Earlier presented algorithms are extended with two new methods. The first method suppresses the non-harmonic signal components caused by drums and percussive instruments by applying principles from RASTA spectrum processing. The second(More)
Music making and listening are a clear example of a human activity that is above all interactive and social, two big challenges for novel HCI paradigms. Nowadays, however, listening to music is usually still a passive, non-interactive experience. Quoting John Sloboda " In highly industrialized societies, we listen to more music, but we make less " [1]. Even(More)