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EE599-2 Audio Signals and Systems

EE599-2 Audio Signals and Systems. Noise Kevin D. Donohue Electrical and Computer Engineering University of Kentucky. 11 10 01 00. Discrete-time Signal. Digital Signal. Analog Signal. Coder. Quantizer. Quantization Noise.

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EE599-2 Audio Signals and Systems

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  1. EE599-2Audio Signals and Systems Noise Kevin D. DonohueElectrical and Computer EngineeringUniversity of Kentucky

  2. 11 10 01 00 Discrete-time Signal Digital Signal Analog Signal Coder Quantizer Quantization Noise Signal amplitudes take on a continuum of values. A discrete signal must be digitized (mapped to a finite set of values) to be stored and process on a computer/DSP

  3. 11 10 01 00 Discrete-time Signal Digital Signal Analog Signal Coder Quantizer Quantization Noise Signal amplitudes take on a continuum of values. A discrete signal must be digitized (mapped to a finite set of values) to be stored and process on a computer/DSP

  4. 11 10 01 00 Analog Discrete Digital Quantization Error and Noise • Quantization has the same effects as adding noise to the signal: • Intervals between quantization levels are proportional to the resulting quantization noise. • For uniform quantization, the interval between signal levels is the maximum signal amplitude value divided by the number of quantization intervals.

  5. Quantization Noise • Original CD clip quantized at 16 bits (blue) and quantized at 6 bits (red)

  6. Quantization Noise Analysis • Assume is a uniformly distributed (amplitude), white, stationary process that is uncorrelated with the signal • Show that the signal to quantization noise ratio for a full-swing range (FSR) sinusoid, quantized with B bit words is approximately:

  7. Reflection Direct Sound SpecularReflected Sound Room Noise For noise generated inside a room will have a frequency dependent propagation, absorption and refection. Thus the room will have a filtering effect on the sound. Sound impinging on surfaces in the room will be absorbed, reflected, or diffused. Absorption Diffusion Heat Transmission Direct Sound DiffuseScattered Sound Direct Sound

  8. Reflection Absorption Effects Reflected and reverberant sounds can become distractions and annoyances. The use of absorbers on reflective surfaces can cut down the reverberation effects in rooms. The model for a signal received at a point in space from many reflections is given as: where nis scaling that represents the attenuation of each reflected signal due to propagation through the air and absorption at each reflected interface and n is the time delay associated with the travel path from the source to the receiver. The signal in the frequency domain is given by:

  9. Reverberant Sound Travel The near or direct field (D) The free or early field (EF1 and EF2) The reverberant or diffuse field (RF1 to RF3)

  10. Decay of Reverberant Sound Field The time it takes for the reverberant sound field to decay by 60dB has become a standard way to characterize room acoustics.

  11. Room Reverberation Time For a space with many randomly distributed reflectors (typically large rooms) reverberation time (RT60 ) is defined as the amount of time for the sound pressure in a room to decrease by 60 dB from its maximum. The time is statistically predicted from the room features with the Sabine equation: where • V is the volume of the room in cubic meters • Si is the surface area of the ith surface in room (in square meters) • aiis the absorption coefficient of ith surface • m is the absorption coefficient of air. Discuss: The relationship between absorption, volume, and RT.

  12. Room Response to White Noise Input Data collected and spectrogram computed by H.L. FournierNote frequency dependence on of decay time.

  13. Example % Create reverb signal [y,fs] = wavread('clap.wav'); % Read in Clap sound % Apply simulated reverb signal yout1 = mrevera(y,fs,[30 44 121]*1e-3,[.6 .8 .6]); taxis = [0:length(yout1)-1]/fs; % Compute envelope of signal env = abs(hilbert(yout1)); figure(1) plot(taxis,20*log10(env+eps)) % Plot Power over time hold on % Create Line at 60 dB below max point and look for intersection point mp = max(20*log10(env+eps)); mp = mp(1); dt = mp-60; plot(taxis,dt*ones(size(taxis)),'r'); hold off; xlabel('Seconds') ylabel('dB'); title('Envelope of Room Impulse Response') % Compute autocorrelation function of envelop and look for peaks % to indicate delay of major echoes maxlag = fix(fs*.5); [ac, lags] = xcorr(env-mean(env), maxlag); figure(2) plot(lags/fs,ac) xlabel('seconds') ylabel('AC coefficient') % Compute autocorrelation function of raw and look for peaks to % indicate delay of major echoes [ac, lags] = xcorr(yout1, maxlag); figure(3) plot(lags/fs,ac) xlabel('seconds') ylabel('AC coefficient') Given the simulated reverb signal compute the RT60. Find the autocorrelation function and try to estimate the delays associated with the major scatterers.

  14. Room Modes The air in a (small) rectangular room has natural modes of vibration given by: where c is the speed of sound in the room p, h, and r are integers 0,1,2, …., and L, W, and H are the length, width, and height of the room.

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