Vishwakarma Institute of Technology
Issue 05 : Rev No. 0 : Dt. 13/03/15
Course Plan Format
Academic Year : _2014-15
Subject Name : Speech and Video processing
Subject Code:
Unit
No.
I
II
Topic
FF No. 182
Branch : Electronics/E&TC
Method
The
speech
production
mechanism, Discrete time speech Lecture
signals, Pole-Zero modeling of
speech ,relevant properties of the
fast Fourier transform and Ztransform for speech recognition,
convolution, linear and non linear
filter banks, spectral estimation of
speech using DFT.
A. Real and Complex Cepstrum,
application
of
cepstral Lecture
analysis to speech signal,
feature extraction for speech,
static and dynamic feature
for
speech
recognition,
robustness
issues,
discrimination in the feature
space, feature selection,
MFCC, LPCC, Distance
measures,
vector
Semester : I
Media
Student Activity
 Tut:
Assessment Tool
i)
Test
I:
Descriptive
type
questions – 80 % ;
Numerical
type
questions – 20 %
ii)Timely
submission
of
completed
home
assignment
iv)
Tutorial
assessment is based
numerical
+
descriptive
i) MCQ based Test
II
 Tut:
Black Board and
ii)Timely
4. MFCC,
power
point
submission
of
5. Vector
presentation
completed
home
Quantization
assignment
HA:
Tutorial
VQ,
distance iii)
assessment
measures , LPCC
numerical
+
descriptive
1. Pole
zero
Black Board
modeling
of
speech signal
Power
point
2. Linear and Nonpresentation
Linear
Filter
bank
3. LPC
HA: FTT, DFT, Power
spectral Density
of
Speech signal
Remarks
Test I out of 30
marks, to be
converted to 10
marks
Test II out of 20
marks, to be
converted to 20
marks
Vishwakarma Institute of Technology
Issue 05 : Rev No. 0 : Dt. 13/03/15
quantization models.
III
IV
V
Video formation, perception and Lecture
representation: Principle of color
video, video cameras, video
display, pinhole model, CAHV
model, Camera motion, Shape
model, motion model, Scene
model, two dimensional motion
models
Optical
flow,
motion
representation,
motion Lecture
estimation
criteria,
optimization methods, pixel
based motion estimation,
Block matching algorithm,
gradient Based, Intensity
matching, feature matching,
frequency domain motion
estimation,
Depth
from
motion.
2D and 3D video tracking, blob
tracking, kernel based counter Lecture
tracking,
feature
matching,
filtering
Mosaicing,
video
 Tut:
Black Board
And Power point
Presentation
i) MCQ bsed Test
HA: Camera Model , II
ii)Timely
motion model
submission
of
completed
home
assignment
iii)
Tutorial
assessment is based
on numerical +
descriptive
i)
End Semester
Examination:
Black Board
Descriptive
Power
point
questions – 75 %
presentation
Numerical
type
questions – 25 %
ii)Timely
submission
of
completed
home
HA:
Block Based
estimation, Depth from assignment
iii)
Tutorial
motion
assessment is based
on numerical based
questions.
Tut:
1. Motion
estimation
2. Frequency
domain motion
estimation
 Tut:
Black Board
Power
Point
Presentaion
i)
End Semester
Examination:
1 Kernel based
Descriptive
tracking
questions – 75 %
type
2. video short Numerical
Vishwakarma Institute of Technology
segmentation, mean shift based,
active shape model, video short
boundary detection.
Issue 05 : Rev No. 0 : Dt. 13/03/15
questions – 25 %
ii)Timely
submission
of
HA:
Motion completed home
assignment
Compensation,
iii)
Tutorial
assessment is based
on numerical +
descriptive
boundary
detection
Levels of Bloom’s Taxonomy applicable for the course – Knowledge / Comprehension / Application / Analysis / Synthesis / Evaluation (Strike out levels not applicable)
List of Reference Books and Text Books -
Text Books:
1. Digital Video processing, A Murat Tekalp, Prentice Hall.
2. Fundamentals of Speech recognition – L. Rabiner and B. Juang, prentice Hall signal processing series
3. Discrete-time speech signal processing: principles and practice, Thmas F. Quatieri, Coth.
Name and Signature of Faculty executing the course plan
1)
Sidharth B. Bhorge
signature of Chairman – BOS
Date : 27/07/2015