A Multipitch Analyzer Based on Harmonic Temporal Structured Clustering

Authors:
Hirokazu Kameoka;Takuya Nishimoto;Shigeki Sagayama
Affiliations:
Graduate Sch. of Inf. Sci. & Technol., Univ. of Tokyo;-;-
Venue:
IEEE Transactions on Audio, Speech, and Language Processing
Year:
2007

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Abstract

This paper proposes a multipitch analyzer called the harmonic temporal structured clustering (HTC) method, that jointly estimates pitch, intensity, onset, duration, etc., of each underlying source in a multipitch audio signal. HTC decomposes the energy patterns diffused in time-frequency space, i.e., the power spectrum time series, into distinct clusters such that each has originated from a single source. The problem is equivalent to approximating the observed power spectrum time series by superimposed HTC source models, whose parameters are associated with the acoustic features that we wish to extract. The update equations of the HTC are explicitly derived by formulating the HTC source model with a Gaussian kernel representation. We verified through experiments the potential of the HTC method