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SOME SIMPLE MANIPULATIONS OF SOUND USING DIGITAL SIGNAL PROCESSING

SOME SIMPLE MANIPULATIONS OF SOUND USING DIGITAL SIGNAL PROCESSING. Richard M. Stern 18-791 demo August 31, 2004 Department of Electrical and Computer Engineering and School of Computer Science Carnegie Mellon University Pittsburgh, Pennsylvania 15213.

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SOME SIMPLE MANIPULATIONS OF SOUND USING DIGITAL SIGNAL PROCESSING

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  1. SOME SIMPLE MANIPULATIONS OF SOUND USING DIGITAL SIGNAL PROCESSING Richard M. Stern 18-791 demo August 31, 2004 Department of Electrical and Computer Engineering and School of Computer Science Carnegie Mellon University Pittsburgh, Pennsylvania 15213

  2. The original sound and its spectrogram

  3. Downsampling the waveform Downsampling the waveform by factor of 2:

  4. Consequences of downsampling • Downsample Original: Downsampled:

  5. Upsampling the waveform Upsampling by a factor of 2:

  6. Consequences of upsampling Original: Upsampled:

  7. Linear filtering the waveform y[n] x[n] Filter 1: y[n] = 3.6y[n–1]+5.0y[n–2]–3.2y[n–3]+.82y[n–4] +.013x[n]–.032x[n–1]+.044x[n–2]–.033x[n–3]+.013x[n–4] Filter 2: y[n] = 2.7y[n–1]–3.3y[n–2]+2.0y[n–3–.57y[n–4] +.35x[n]–1.3x[n–1]+2.0x[n–2]–1.3x[n–3]+.35x[n–4]

  8. Filter 1 in the time domain

  9. Output of Filter 1 in the frequency domain Original: Lowpass:

  10. Filter 2 in the time domain

  11. Output of Filter 2 in the frequency domain Original: Highpass:

  12. Pitch Pulse train source Vocal tract model Noise source The source-filter model of speech A useful model for representing the generation of speech sounds: Amplitude p[n]

  13. Separating the vocal-tract excitation from the filter • Original speech: • Speech with 75-Hz excitation: • Speech with 150-Hz excitation: • Speech with noise excitation:

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