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Introduction to Spectral Analysis Phil Lockett Centre College KAPT meeting March 16, 2013

Introduction to Spectral Analysis Phil Lockett Centre College KAPT meeting March 16, 2013. Any Time Signal can be represented by Sums of Cosines and Sines. The signal can be represented in either the. Time Domain. or. Frequency Domain. Time Domain. Frequency Domain. PRAAT .

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Introduction to Spectral Analysis Phil Lockett Centre College KAPT meeting March 16, 2013

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  1. Introduction to Spectral Analysis Phil Lockett Centre College KAPT meeting March 16, 2013

  2. Any Time Signal can be represented by Sums of Cosines and Sines The signal can be represented in either the Time Domain or Frequency Domain

  3. Time Domain Frequency Domain

  4. PRAAT

  5. Spectrogram is the Frequency Spectrum as a function of Time Frequency Time

  6. Chirp

  7. Tuning Fork Time Signal

  8. Tuning Fork Frequency Spectrum 465.82 1/s 931.65 1/s

  9. Jeff Lucas - Purdue Sound input (nuthatch ‘quank’) time (sec) 0.12 AEP dBnV 10k Spectrogram of AEP Hz time (sec) 0.12

  10. [A] [i] [u]

  11. Vowel Formant Average Spectrograms

  12. Me saying “ee”

  13. Power Spectrum for “ee” 1 – 127.2 Hz 2 – 254.4 Hz skip to 20 – 2544 Hz Vocal Fold Harmonics:

  14. “ee” “ah”

  15. The Vowel or [ə] “schwa”

  16. Use “schwa” Frequencies to measure Vocal Tract Length By Modeling Vocal Tract as Uniform Tube

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