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This paper presents a new multiplicative algorithm for nonnegative matrix factorization with β-divergence. The derived update rules have a similar form to those of the conventional multiplicative algorithm, only differing through the presence of an exponent term depending on β. The convergence is theoretically proven for any real-valued β based on the(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)
This paper presents a new sparse representation for polyphonic 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)
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)
The Music Instrument Identification research is an important and difficult problem in Music Information Retrieval (MIR). In this paper an algorithm based on flexible harmonic model is proposed to represent the pitch in music by Gaussian mixture structure. The proposed algorithm models each spectral envelope of underlying harmonic structure to approximate(More)
There is currently a big demand for automating big data analysis. In the data analysis field, data abstraction or summarization playes an important role in the extraction of generalized information from large scale data. We developped an artificial intelligence computer system with the aim of automating big data analysis and came up with a method that can(More)
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