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SP Question Bank

The document contains questions related to speech signal processing techniques including short time Fourier transform, discrete Fourier transform, spectrograms, formant analysis, liftering, mel frequency cepstral coefficients, cepstrum, and applications of these techniques. The questions cover topics such as the advantages of short time Fourier transform and FIR filters for speech analysis, how window duration affects discrete Fourier transform output, the use of pre-emphasis and log spectra in speech analysis, types of liftering, comparisons of short time Fourier transform and Fourier transform, definitions of cepstrum, mel frequency cepstral coefficients, power cepstrum and complex cepstrum, and applications that use mel frequency cepstral coefficients.

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Pratibha Gandhi Dumane
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70 views2 pages

SP Question Bank

The document contains questions related to speech signal processing techniques including short time Fourier transform, discrete Fourier transform, spectrograms, formant analysis, liftering, mel frequency cepstral coefficients, cepstrum, and applications of these techniques. The questions cover topics such as the advantages of short time Fourier transform and FIR filters for speech analysis, how window duration affects discrete Fourier transform output, the use of pre-emphasis and log spectra in speech analysis, types of liftering, comparisons of short time Fourier transform and Fourier transform, definitions of cepstrum, mel frequency cepstral coefficients, power cepstrum and complex cepstrum, and applications that use mel frequency cepstral coefficients.

Uploaded by

Pratibha Gandhi Dumane
Copyright
© © All Rights Reserved
We take content rights seriously. If you suspect this is your content, claim it here.
Available Formats
Download as DOCX, PDF, TXT or read online on Scribd
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Reference Questions

Questions (2m)

1. What is short time Fourier transform? Why is it suited for analysis of speech signals?
2. What are the advantages of using FIR filters for designing speech filter banks?
3. Explain how duration of the windows affects the output analysis for the discrete
Fourier transform. What features should the window have?
4. How can pre-emphasis help speech analysis?
5. Explain how the durations of the window affects the output of the analysis for the
discrete Fourier transform
6. Explain application of FIR filters in speech processing.
7. What is a spectrogram?
8. What are the applications of a spectrogram?
9. What is the need of short time Fourier analysis?
10. What do you understand by convolved spectra?
11. How formants are estimated using log spectrum?
12. What are the different types of liftering?
13. What are the advantages of short and long windows?
14. Compare STFT with FT.
15. What is a cepstrum? What are the operations required to enter the cepstral domain?
16. What is liftering in speech processing?
17. What is MFCC?
18. What are the applications where MFCCs are used?
19. Define power cepstrum.
20. Define complex cepstrum.
21. Draw the flowchart for computing cepstrum.
22. Compare MFCC and PLP.

Questions (5m)

1. Explain the linear filter interpretation of short time Fourier transforms.


2. Explain the Fourier transform interpretation of STFT.
3. A speech signal is sampled at a rate of 20000 samples / sec. A sequence of length (N)
1024 samples is selected and the 1024 point DFT is computed.
4. What is the time duration of the segment of speech?
5. What is the frequency resolution (spacing in Hz) between the DFT values?
6. Discuss the properties of Homomorphic systems for convolution.
7. If L=200 samples/frame and Fs = 20KHz calculate
i) sampling rate of Xn(ejw)
ii) bandwidth of the window
8. Write a note on : Spectrographic Displays
9. Write a note on spectrographic analysis of speech signal. What are the typical values
of parameters (e.g. window duration, FFT length, and window shift) for wideband and
narrowband spectrograms? Give the reasoning for the same.
10. With respect to time windows for speech analysis, to what type of filter should the
spectrum of a window correspond? Explain how the bandwidth of an analysis window
affects the spectrographic estimation of formants and F0.
11. Specify properties of homomorphic systems for convolution with related equations.
Draw the block diagram for representing homomorphic system for i) convolution ii)
de-convolution.
12. Explain pitch period estimation in cepstral domain.
13. Explain measurement of formant frequencies using a cepstrum.
14. Explain pitch estimation based on FFT analysis of speech signal.
15. What is complex cepstrum of speech? Specify its properties with related equations.
16. Explain the measurement of formant frequencies using the log spectrum
17. Explain the method to separate the impulse response of the vocal tract from the
speech signal. Draw the block schematic and explain the function of each block.

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