Acoustic and Auditory Phonetics Review: Chapters 1-5
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1 Acoustic and Auditory Phonetics Review: Chapters 1-5 Jeffrey Heinz University of Delaware March 15, /21
2 Outline Acoustics & Filters Acoustics of Speech Digital Signal Processing 2/21
3 Basic Acoustics & Filters 1. What is sound? 2. How does sound from a source reach your ears? 3. Types of sounds 4. Acoustic filters 3/21
4 Types of Sounds 1. Simple periodic waves 2. Complex periodic waves 3. Aperiodic waves (white noise, impulse noise) 4/21
5 Simple Periodic Waves Pressure sin(x*6.28) Time (ms) Amplitude Period, Frequency, and Wavelength Phase 5/21
6 Pressure Complex Periodic Waves A+B Time (ms) A C A+C Fourier Synthesis Fourier Analysis 6/21
7 Power Spectra A+B A C A+C A spectrum Pressure Amplitude Time (ms) Frequency (Hz) Fourier Synthesis Fourier Analysis 7/21
8 Filters 4 A band pass filter (rectangular) 4 A band pass filter (smoothed) 3 3 Amplitude 2 Amplitude Frequency (Hz) Frequency (Hz) Filters pass certain frequencies and block others. Bandwidth 8/21
9 Outline Acoustics & Filters Acoustics of Speech Digital Signal Processing 9/21
10 1. Source Filter Theory 2. Resonant frequencies 3. Tube models of schwa 4. Standing wave patterns 10/21
11 Source Filter Theory 11/21
12 Harmonics and resonant frequencies 12/21
13 Uniform tube open at one end is like Calculating resonant frequencies Tube closed at both ends f k = kc 2L (1) Tube closed at one end and open at the other f k = (2k 1)c 4L (2) 13/21
14 Standing Wave Patterns 14/21
15 Standing Wave Patterns 14/21
16 Outline Acoustics & Filters Acoustics of Speech Digital Signal Processing 15/21
17 Digital Signal Processing 1. Digitizing sound 2. Processing sound 16/21
18 Digitizing Sound 1. Sampling rate (making time discrete) 2. Quantization (making amplitude discrete) 17/21
19 Processing sound 1. Digital Filters removes low or high frequency components from the signal 2. Autocorrelation tracks pitch changes over time 3. RMS amplitude measures acoustic intensity (loudness) 4. Fast Fourier Transform decomposes complex waves into their simple component parts 5. Linear Predictive Coding allows examination of broad spectral peaks 6. Spectrograms shows spectral changes over time All of the above rely on Windowing 18/21
20 Windowing 1. Speech is understood to be a sequence of complex periodic waves 2. The signal within each window is treated as a periodic complex wave. 3. Window length and window shape 19/21
21 Limits of digital signal processing 1. Nyquist frequency 2. Aliasing effects 3. Time resolution vs. frequency/amplitude resolution 20/21
22 Units and Vocabulary Hertz milleseconds seconds samples... peak-to-peak amplitude quantization noise fundamental frequency compression rarefaction cycles harmonics resonant frequencies formants lag duration signal-to-noise ratio... 21/21
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