A Multipitch Analyzer Based on Harmonic Temporal Structured Clustering
| Autor: | Hirokazu Kameoka, Shigeki Sagayama, Takuya Nishimoto |
|---|---|
| Rok vydání: | 2007 |
| Předmět: |
Spectrum analyzer
Audio signal Acoustics and Ultrasonics Computer science Speech recognition Spectral density computer.software_genre symbols.namesake Kernel method Condensed Matter::Superconductivity Gaussian function symbols Electrical and Electronic Engineering Cluster analysis Audio signal processing computer Gaussian process Algorithm Computer Science::Distributed Parallel and Cluster Computing |
| Zdroj: | IEEE Transactions on Audio, Speech and Language Processing. 15:982-994 |
| ISSN: | 1558-7916 |
| DOI: | 10.1109/tasl.2006.885248 |
| Popis: | 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 |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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