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【音乐应用的音频信号处理】课程目录

【音乐应用的音频信号处理】课程目录

作者: 莹子说她想吃烤冷面 | 来源:发表于2019-10-11 13:48 被阅读0次

    《音乐应用的音频信号处理》(Audio Signal Processing for Music Applications),这个课是斯坦福的CCRMA和Universitat Pompeu Fabra of Barcelona合开的,其中斯坦福的那个老师是开源重采样库libresample的作者,一些著名开源DAW都了这个库。
    课程链接

    目录:

    1. Introduction
      ● Introduction to Audio Signal Processing
      ● Course outline
      ● Basic mathematics
          - Sinusoidal functions
          - Complex numbers
          - Euler’s formula
          - Complex sinusoids
          - Scalar product of sequences
          - Even and odd functions
          - Convolution

    2. Discrete Fourier transform
      ● DFT equation
      ● Complex exponentials
      ● Scalar product in the DFT
      ● DFT of complex sinusoids
      ● DFT of real sinusoids
      ● Inverse-DFT

    3. Fourier transform properties
      ● Linearity, shift, symmetry, convolution
      ● Energy conservation and decibels
      ● Phase unwrapping, zero padding
      ● Fast Fourier Transform (FFT)
      ● FFT and zero-phase windowing
      ● Analysis/synthesis

    4. Short-time Fourier transform
      ● STFT equation
      ● Analysis window
      ● FFT size and Hop size
      ● Time-frequency compromise
      ● Inverse STFT

    5. Sinusoidal model
      ● Sinusoidal model equation
      ● Sinewaves in a spectrum
      ● Sinewaves as spectral peaks
      ● Time-varying sinewaves in spectrogram
      ● Sinusoidal synthesis

    6. Harmonic model
      ● Harmonic model equation
      ● Sinusoids-partials-harmonics
      ● Monophonic/polyphonic signals
      ● Harmonic detection
      ● Fundamental frequency detection

    7. Sinusoidal plus residual modeling
      ● Stochastic model
      ● Stochastic approximation of sounds
      ● Sinusoidal/harmonic plus residual model
      ● Residual subtraction
      ● Sinusoidal/harmonic plus stochastic model
      ● Stochastic model of residual

    8. Sound transformations
      ● Short-time Fourier transform
          – Filtering; morphing
      ● Sinusoidal model
          – Time and frequency scaling
      ● Harmonic plus residual model
          – Pitch transposition
      ● Harmonic plus stochastic model
          – Time stretching; morphing

    9. Sound/music description
      ● Spectral-based audio features
      ● Description of sound/music events and collections

    10. Concluding topics
      ● Review of class
      ● Beyond audio signal processing for music applications

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