Yu Kitano

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This paper presents a new sparse representation for poly-phonic music signals. The goal is to learn the time-varying spectral patterns of musical instruments, such as attack of the piano or vibrato of the violin in polyphonic music signals without any prior information. We model the spectrogram of music signals under the assumption that they are composed of(More)
This paper discusses a method for monophonic instrument sound separation based on nonnegative matrix factoriza-tion (NMF). In general, it is not easy to classify NMF components into each instrument. By contrast, monophonic instrument sound gives us an important clue to classify them, because no more than one sound would be activated simultaneously. Our(More)
In this paper, we propose a new method of blind source separation (BSS) for music signals. Our method has the following characteristics: 1) the method is a combination of the sparseness-based model of source signals and the factorized basis model in nonnegative matrix factorization (NMF), 2) it is assumed that only one basis which structure source signals(More)
Multipitch estimation is an important and difficult problem in entertainment computing. In this paper a flexible harmonic temporal structure for modeling musical instrument was proposed for estimating pitch in real music. Unlike the previous research, the proposed model does multipitch estimation according to the specific characteristics of specific musical(More)
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