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Electronics & Communications
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Speech Signal Processing Laboratory
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Linear Prediction Analysis
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Linear Prediction Analysis
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Aim
Theory
Procedure
Simulation
Quiz
Assignment
Slot Booking
Reference
Feedback
1)
In which domain the LP analysis deconvolve the speech into excitation and vocal tract components
Frequency domain.
Time domain.
Quefrency domain.
Time-frequency domain.
2)
How LP residual is computed from the LP coefficients
By inverse filtering of speech using LP coefficients.
By LP filtering of the speech using LP coefficients.
By low-pass filtering of speech using the LP coefficients.
By high pass filtering of speech using LP coefficients
3)
The LP coefficients for a given segment of speech is computed by
Auto regression.
Cross correlation.
Autocorrelation method.
moving average method.
4)
How the pitch is computed by the LP analysis
From the autocorrelation of LP residual.
From the LP spectrum.
From the autocorrelation of the LP spectrum.
From the cross correlation of the LP residual with the speech signal
5)
How the formant locations are estimated by LP analysis
From LP residual.
From LP spectrum.
From the LP residual spectrum.
Autocorrelation of LP residual.
6)
The normalized error curves are used to determine
The optimal prediction order for LP analysis.
Pitch of the given speech segment.
Formant locations of the given speech segment .
Energy in the speech signal.
7)
The nature of the normalized error curve is
Monotonically decreasing.
Monotonically increasing.
Sinusoidal.
Gaussian.
Cite this Simulator:
vlab.amrita.edu,. (2011). Linear Prediction Analysis. Retrieved 4 May 2024, from vlab.amrita.edu/?sub=59&brch=164&sim=616&cnt=1780
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