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SHS 375 EXAM 1 PRACTICE TEST QUESTIONS AND ANSWERS 100% VERIFIED

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  • Course
  • SHS 375
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  • SHS 375

SHS 375 EXAM 1 PRACTICE TEST QUESTIONS AND ANSWERS 100% VERIFIED Sampling - Answer- taking samples at given intervals-energy between sampling points is discarded- analog signal is made discrete in time. Acceptable sampling rate? - Answer- Nyquist's sampling theorem, the number of samples need...

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  • November 7, 2024
  • 8
  • 2024/2025
  • Exam (elaborations)
  • Questions & answers
  • SHS 375
  • SHS 375
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Scholarsstudyguide
SHS 375 EXAM 1 PRACTICE TEST 2024-
2025 QUESTIONS AND ANSWERS 100%
VERIFIED

Sampling - Answer- taking samples at given intervals-energy between sampling points
is discarded- analog signal is made discrete in time.

Acceptable sampling rate? - Answer- Nyquist's sampling theorem, the number of
samples needed is TWICE the highest frequency of interest

Example acceptable sampling rate: interested in frequencies up to 5000 Hz, sampling
rate would have to be... - Answer- At least twice that, 10000 Hz

Why do we have to do sampling rate at twice the highest frequency of interest? -
Answer- to avoid aliasing

Aliasing - Answer- happens when higher frequencies appear as "fake" lower
frequencies (aka aliases). usually due to undersampling and lack of low-pass filtering

How to avoid aliasing - Answer- determine highest frequency of interest, filter energy
above the highest frequency of interest, sample the signal at a rate that is at least twice
as high as the highest frequency of interest.

Typically for speech application, recommended sampling frequency is - Answer- 22050
Hz (standard rate)

Quantization - Answer- converts the amplitude or energy level of the samples,
amplitude of signal is made discrete, continuous amplitude variations need to be
represented.

Quantum - Answer- is an increment of energy

Quantiziation rate - Answer- aka resolution, measured in bits.

*Bits are - Answer- binary digits (0,1) so a 1 bit system has 2 levels. and 8 bit system
has 256 levels. Levels equal 2 to the ^nth power (example 2^8th=256)

Analog to Digital Conversion picture - Answer- (acoustic signal)=> pre-emphasis filter=>
(pre-emphasis signal)pre-sampling low-pass filter=> (filtered

, signal)sampler=>(sequence of samples) quantizer=> (quantized samples)encoder =>
(coded item)
()= dotted lines on picture

what's involved in A-to-D and D-to-A conversion? - Answer- needs to be converted back
to analog form, final low-pass filtering is needed to smooth out the signal

To listen to a recording it needs to be in what form? - Answer- analog

time waveform presents the amplitude of the signal as ... - Answer- a function of time
(y=amplitude and x = time)

Frequency - Answer- the number of times an object vibrates through a complete cycle
per second, measured in hertz-Hz

Period - Answer- the length of one cycle

measuring frequency - Answer- 1/time in seconds Ex: duration(time) .01 frequency
would equal 100Hz because 1/.01=100

shorter period - Answer- higher frequency

Spectrum - Answer- presents amplitude of the signal as a function of frequency
(amplitude =y, frequency = x). Does NOT have a temporal component , useful for
looking at the magnitude at various frequency components at a specific time, NOT
useful to view how signal changes over time

Main types of spectra for speech analysis... - Answer- FFT, LPC

LCP - Answer- linear predictive coding

FFT - Answer- fast fourier transform

FFT components - Answer- decomposes a signal into its frequency components, is an
algorithm that greatly expedites the computations required for a more precise discrete
fourier transform, useful for looking at all frequency components, increasing the FFT
points allow more accurate display

FFT display - Answer- amplitude is on the y axis, frequency is on the x, line represents
frequency components and their amplitudes

LPC components - Answer- a method that attempts to predict upcoming speech
samples based on a weighted sum of previous samples, uses estimation based on a
vocal tract model filter, not as precise as FFT, useful for looking at spectral peaks but
not detailed frequency components, increasing the LPC order and FFT points changes
the display

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