Parametric Time-Frequency Analysis and Its Applications in Music Classification

Parametric Time-Frequency Analysis and Its Applications in Music Classification

Analysis of nonstationary signals, such as music signals, is a challenging task. The purpose of this study is to explore an efficient and powerful technique to analyze and classify music signals in higher frequency range (44.1 kHz). The pursuit methods are good tools for this purpose, but they aimed at representing the signals rather than classifying them as in Y. Paragakin et al., 2009. Among ...

Applications of Operator Theory to Time- Frequency Analysis and Classification

Jack McLaughlin and Les E. Atlas Interactive Systems Design Laboratory, Department of Electrical Engineering University of Washington, Box 352500, Seattle, WA 98195-2500, U.S.A. jackm | [email protected] phone: (206) 6851315 (Atlas) EDICS # SP 2.3.1 Abstract — An entirely new set of criteria for the design of kernels (generating functions) for time-frequency representations (TFRs) is p...

Time-Frequency Analysis and Its Applications to Multimedia Signals

Time-Frequency Reassignment for Music Analysis

Time-frequency reassignment may be viewed as a refinement of the short-time Fourier transform, in which phase information is used to reduce the smearing of energy associated with the standard spectrogram. However, even given the perceptibly clearer visual representation yielded by the reassignment method in the case of musical signals, the task remains of extracting useful information from it f...

Time - Frequency Analysis of Music Mentor : Yeon

Use the Fast Wavelet Transform to analyze two music signals. Compare at least four different wavelet systems, e.g. HAAR, BIOR7/9, DAUB16, Coiflet3, or Coiflet4. Choose two different signals for your analysis. One signal should be from a single source with well structured frequency content, for example a recording of a xylophone. You are encouraged to find the sources on your own, but ask for as...