Homework 3 Problems Unsolved - Automatic Speech Processing | EEL 6586, Assignments of Electrical and Electronics Engineering

Material Type: Assignment; Professor: Harris; Class: AUTOMATIC SPEECH PROC; Subject: ENGINEERING: ELECTRICAL; University: University of Florida; Term: Spring 2003;

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Pre 2010

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EEL6586: Automatic Speech Processing HW#3
EEL 6586: HW#3
Assignment is due Friday, Feb 14, 2003 in class. Late homework
loses e#of days late 1percentage points. See the current late penalty
at http://www.cnel.ufl.edu/hybrid/harris/latepoints.html
This assignment includes both matlab and textbook questions.
PART A: Textbook problems
A1 An infinite train of impulses is created with the following relation
e(n) = X
k
δ(n+kP )
Assume that the sampling frequency is 10kHz.
1. Determine the value of P to create a pitch frequency of 100Hz.
2. The infinite train of impulses is fed through an all-pole model of
H(z) = 1/(1 + .9z1+.81z2)
What is the dominant formant frequency in the signal?
3. Is this formant frequency higher or lower than typical first formant
frequencies for humans?
4. How will the formant frequency change if pre-emphasis is applied
to the signal (s(n)0.95s(n1))?
A2 Assume that an infinite impulse train
X
k
δ(n+kP )
is filtered by a vocal-tract model given by H(z) = 1/(1+.9z1+.81z2)
to produce a speech signal s(n).
1. Derive the difference equation for s(n).
2. Compute the autocorrelation function r(0) for the speech signal
s(n).
3. Compute the autocorrelation function r(1) for the speech signal
s(n).
J.G. Harris January 31, 2003 1
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EEL 6586: HW#

Assignment is due Friday, Feb 14, 2003 in class. Late homework loses e#^ of^ days late^ − 1 percentage points. See the current late penalty at http://www.cnel.ufl.edu/hybrid/harris/latepoints.html

This assignment includes both matlab and textbook questions.

PART A: Textbook problems

A1 An infinite train of impulses is created with the following relation

e(n) =

k

δ(n + kP )

Assume that the sampling frequency is 10kHz.

  1. Determine the value of P to create a pitch frequency of 100Hz.
  2. The infinite train of impulses is fed through an all-pole model of

H(z) = 1/(1 +. 9 z−^1 +. 81 z−^2 )

What is the dominant formant frequency in the signal?

  1. Is this formant frequency higher or lower than typical first formant frequencies for humans?
  2. How will the formant frequency change if pre-emphasis is applied to the signal (s(n) − 0. 95 s(n − 1))?

A2 Assume that an infinite impulse train ∑

k

δ(n + kP )

is filtered by a vocal-tract model given by H(z) = 1/(1+. 9 z−^1 +. 81 z−^2 ) to produce a speech signal s(n).

  1. Derive the difference equation for s(n).
  2. Compute the autocorrelation function r(0) for the speech signal s(n).
  3. Compute the autocorrelation function r(1) for the speech signal s(n).
  1. Compute the single LPC coefficient (p = 1) for this system.
  2. How does this coefficient compare to the first coefficient when p = 2? Explain.

A3 Assume that white noise excitation w(n) is filtered by an all-pole vocal- tract model H(z) = 1/(1 +. 25 z−^2 ) to produce a speech signal s(n). w(n) is defined:

E{w(n)w(m)} =

{ 1 m = n 0 m 6 = n

In this problem you will use LPC to derive an all-pole approximation to H(z).

  1. Derive the difference equation for s(n).
  2. Compute the autocorrelation function r(0) for the speech signal s(n).
  3. Compute the autocorrelation function r(1) and r(2) for the speech signal s(n).
  4. Compute the first two LPC coefficients (p = 2).
  5. (5 points) Derive Hˆ(z), the all-pole approximation to H(z). Does your answer make sense?

A4 Problem 5.7 in Quatieri

A5 (for extra credit) Prove that the 3db bandwidth of a formant caused by a single dominant pole can be approximated by

bw ≈ − ln(r)fs/π

where r is the distance of the pole to the origin and fs is the sampling frequency in Hz.

PART B: Short Answer

B1 Give an example of a voiced fricative and also suggest an English word that contains that voiced fricative.

C4 Write a procedure that automatically computes the pitch by finding the ”first biggest peak” after the lag zero peak. What pitch is detected for your example window?

C5 Put all of the pieces together and write an algorithm to compute pitch for each window Write a program that determines the pitch of each window of a sentence (if the pitch exists). Show a plot of F0 (in Hz) vs. time (in seconds). You may need to add an additional filtering step to smooth out the pitch values. Indicate unvoiced regions and silence with a pitch of zero. Hand in plots showing the results on the two sentences

As always, hand in all of your matlab code as the appendix of your home- work. Discuss your algorithms in detail and comment on the accuracy of your algorithms.