Jarno Seppänen

Learn 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)
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)
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)
  • 1