II Semester M.E. (Electronics & Communication) Degree Examination, July 2014 (2K9 Scheme) EL 215.4 : Elective – I : SPEECH AND AUDIO SIGNAL PROCESSING Time : 3 Hours
Max. Marks : 100
Instruction : Answer any five full questions. 1. a) Write a block diagram to illustrate speech production mechanism. Discuss the significance of source and filter in the context of producing vowels, fricatives and plosives sounds. b) Write a note on : Spectrograms.
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c) Discuss the following speech sounds in terms of source, filter, places and manner of articulation : i) Nasals and ii) Diphthongs. Give an example for each.
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2. a) Define short time energy and short time average zero crossing rate.
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b) Discuss speech Vs silence discrimination algorithm based on short time energy and short time average zero crossing rate. Indicate the limitation of the technique.
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c) Discuss the significance of short time autocorrelation function and 3 level central clipper in the context of speech signal processing.
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3. a) Explain short time Fourier transform and give its filter bank interpretation in terms of low pass and band pass filters.
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b) Discuss the overlap and add method of short time synthesis and derive the expression for necessary constraints.
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c) Show that short time autocorrelation function and short time psd form a Fourier transform pair.
6 P.T.O.
JEP – 1056
-2-
*JEP1056*
4. a) State and prove any two properties of complex cepstrum by considering rational z-transform of the form. |A|∏
X (z) =
(∏
Ni
Mi k =1
k =1
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(1 − a kz −1) ∏M0 (1 − bkz) k =1
. (1 − ckz −1)) (∏N0 (1 − dkz)) k =1
b) Find the complex and real cepstrum of the sequence p(n) = δ(n) +
1 1 δ(n − 25 ) + δ(n − 50 ) . 2 4
c) Explain with a block diagram steps involved in computing the real cepstrum of a speech signal. Draw a block diagram to explain how formants of the speech signal are estimated from the computed cepstrum and justify the steps.
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5. a) Define a pth order linear predictor. Show that the following relation holds for a pth order linear predictor s (n) =
p
∑k=1aks(n − k) + e(n), where {ak} are LP
coefficients and e (n) is the prediction error.
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b) Explain the autocovariance method of LP analysis and show that i)
p
∑k =1α kφn( i − k ) = φn (i, 0),
1 ≤ i ≤ p, and assuming p = 4, write the above
equation in the matrix form. ii) the diagonal elements of the matrix are given by, φn(i + 1, k + 1) = φn(i, k) + sn(− i − 1)sn(− k − 1) − sn(N − 1 − i)sn (N − 1 − k ) .
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c) Using Durbin’s recursive algorithm compute the transfer function of 2nd order LP model for a speech signal whose autocorrelation sequence is R(k)= (24/5) × 2–|k| – (27/10) × 3–|k|. 6. a) Explain the concept of masking in the context of speech perception.
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b) Explain how VQ techniques can be applied to classify speech vectors.
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c) Explain 3 different groups of speech coders.
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*JEP1056*
-3-
JEP – 1056
7. a) With a block diagram explain ADPCM system with feed-forward adaptive quantization. b) Write a note on : i) LD_CELP G.728 speech compression standard. ii) MPEG audio compression algorithm.
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(6+8)
8. Write short notes on : i) Mel frequency cepstral coefficients. ii) Hidden Markov model, and iii) Text to speech synthesis. __________________
... Enâ1 + x2 (n),where the window h (n), is defined as h (n) = anu(n), x (n) is. the speech signal, and 0 < a < 1. Draw a digital network diagram of this equation. 6.
5. What are diphthongs? 6. Why we require sampling of analog signals? 7. Why we generally keep sampling frequency more than Nyquist rate for sinusoidal. signals? 8. What are the assumptions uses while designing a uniform quantizer? 9. What are the ad
as VisualStudio, GCC, Eclipse, Pycharm and has undertaken audio signal processing course. Page 1 of 1. JD_ Audio signal processing.pdf. JD_ Audio signal ...
from any use or operation of any methods, products, instructions, or ideas contained in the material herein. British Library Cataloguing in Publication Data.
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Sep 14, 2007 - inputted to the analysis filter bank. The di?'erences between the reconstructed audio sound track and the original sound track can be made ...
on each new speaker approaching that of an SD system for that speaker, while ... over the telephone, one can only count on a few seconds of unsupervised speech. ... The authors are with the Panasonic Speech Technology Laboratory, Pana-.
voice approach with other speaker adaptation algorithms, the ...... the 1999 International Conference on Acoustics, Speech, and Signal Processing. He was an ...
We are looking for two doctoral students for the ICHO project (Immersive Concerts for. Homes). The aim of the project is to bring the immersive concert experience to people's homes with the help of head-tracked headphones and sophisticated signal pro
performance for clean and noisy images but also audio-visual speech recognition ..... [4] Ross, L. A., Saint-Amour, D., Leavitt, V. M., Foxe, J. J. Do you see what I ...
Email: {asubram, sabrig, epatter, jgowdy}@clemson.edu. Abstract. In recent years ... visual information for the purposes of Automatic Speech. Recognition (ASR) ...
Department of Electrical and Computer Engineering. Clemson University ..... Interaction,â PhD Dissertation, University of Illinois, Urbana-. Champaign, 1999.
