Home
Project
Workshop
Nodal Centres
Apply for Nodal Centre Program
Nodal Centre List
Free online demo
Nodal Centre Inaugurations
Unique Login ID
News & Events
Publications
Survey
Faculty Survey
Student Survey
Contact us
Login
.
you are here->
home
->
Biotechnology and Biomedical Engineering
->
Speech Signal Processing Laboratory
->
Short-Term Frequency Domain Processing of Speech
.
.
Short-Term Frequency Domain Processing of Speech
.
.
Aim
Theory
Procedure
Pre Quiz
Simulation
Post Quiz
Assignment
Slot Booking
Reference
Feedback
1)
The log magnitude spectrum as compared to linear magnitude spectrum has better visibility of
High frequency components
Low frequency components
Mid frequency components
None of the above
2)
As plotted in figure 1, the limitating of DTFT of speech signal is
Only high frequency components are visible
Only low frequency components are visible
Timing information is missing
Presence of two sided spectrum
3)
As plotted in Figure 2, the spectrum of voiced and unvoiced segments differ in
Trend in the spectrum
Presence and absence of pitch & harmonics structure
Both first and second choices
Only second choice
4)
The STFT of the speech signal in Figure 3, has hilly structures at different frequencies across time indicating
Time varying nature of spectral information
Time invariant nature of spectral information
Time varying amplitude in the speech signal
High frequency regions in the speech signal
5)
Compared to true spectrum, the convolved spectrum observed in Figure 4, is different in term of
Reduction of spectral amplitude in the main lobe
Leakage of spectral amplitude into the side lobes
Both first and second choices
Only second choice
6)
As given in Figure 5, compared to rectangular,hamming and hanning window functions have
Reduced main lobe amplitude
Increased main lobe width
Increased peak to side lobe ratio
All of the above
7)
While performing spectral analysis of speech using window functions ,
Speech is applied with window function and then spectrum is computed
Spectrum is computed and then window function is applied
Window function is applied while observing a particular frequency component
Independent of window function
8)
The difference in the short term spectra of voiced and unvoiced segments for different windowing functions is
Size of window
Type of window
Both size & type of window
Under enhance of window functions
9)
As given in Figure 8, the increase in the size of the window functions increases
Spectral resolution
Looses timing information
Smoothing of the spectral information
All of the above
Cite this Simulator:
vlab.amrita.edu,. (2012). Short-Term Frequency Domain Processing of Speech. Retrieved 1 November 2024, from vlab.amrita.edu/?brch=164&cnt=2905&sim=908&sub=3
.....
.....
.....
Copyright @ 2024 Under the NME ICT initiative of MHRD
Powered by
Amrita
Virtual Lab Collaborative Platform
[ Ver 00.13. ]