... audio compression algorithm. (6+8). 8. Write short notes on : i) Mel frequency cepstral coefficients. ii) Hidden Mar
*JEP1056*
JEP – 1056
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.
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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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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. __________________
