SGN-4227 Digital Audio Processing and Analysis

LAB. EXERCISES AND LECTURE NOTES


-j0299171  Course Topic

The objective of this course is to provide students with fundamental knowledge about various signal processing techniques applied to digital audio signals. All of this knowledge is essential to the understanding of the function of present day digital audio processing systems and form a strong foundation of the learning of newly developed digital devices/systems with applications to audio signals. Thus this course serves as an introductory course to other more advanced digital audio processing.

- Lecturer: Dr. Serkan Kiranyaz (Office TC 432)     E-mail addresses name.surname@tut.fi

- There will be 14 lectures (TB-214) and 14 Lab. exercises (TC 303) 

j0332364            The “official” course web page is located at:

http://www.cs.tut.fi/~serkan/SGN-4227

 

Important Note: Lab. reports will only be considered for those students who attend to that Lab.

    LECTURE NOTES:

Topic

Notes

Date

Lecture 01 - Introduction

 

DASP Overview, Sound waves, Fundamentals of Acoustics, Digital Signals

Lecture1  [zip]

 

 

02.09.2011

Lecture 02 – Signal Processing Review

LTI Systems, Convolutions, Probability Theory and Random Process.

 

 

 

Lecture 03/04 – Signal Processing Review

Fourier Family, Sampling

 

 

 

Lecture 05/06 – Digital Audio: AD/DA Conversions

 

Quantization, AD/DA, Dither, PCM, Delta-sigma modulation, Quantization, Quantization Error, Noise Shaping

 

 

 

Lecture 07/08 – Audio Analysis and Synthesis: Short Time Fourier Transform

STFT, Sub-band Filtering, Filter Bank Summation, Overlap Addition (OLA) Method

 

 

Lecture 09/10 – Audio Enhancement

De-noising, Audio Filter Design, Low/High Pass Filters, Wiener Filter

 

 

Lecture 11 – Perceptual Audio 

Loudness and Masking, Psychophysical Laws, Psychoacoustics, Critical Bands, Masking

 

 

 

Lecture 12/13 – Audio Coding and Standards

PCM, DPCM, Sub-band filtering and quantization, LPC coder, Perceptual audio coding:  MPEG-Audio

 

 

Lecture 14 – Audio Analysis, Features and Retrieval

Audio Feature Extraction – Acoustic Features, MFCC, Audio Classification and Segmentation

 

 


 j0293570  The exercise sheets and additional materials will be published below in PDF format on Thursdays of the week.

 

Exercise Sheets

Additional Material

Date

Exercise-1

Introduction to plots in Matlab

  Lab-1 [zip]

Notes-1 [zip]

http://www.math.ufl.edu/help/matlab-tutorial/

http://www.maths.dundee.ac.uk/~ftp/na-reports/MatlabNotes.pdf

http://www.math.mtu.edu/~msgocken/intro/intro.html 

 

 

 

02.09.2011

Exercise-2

Convolution

 

 

Exercise-3

Spectral Analysis

 

 

Exercise-4

Windowing & Sampling

 

 

Exercise-5

Sampling & Aliasing

 

 

Exercise-6

Short-time frequency analysis

 

 

 

 

 

 

Closed Book QUIZ

Pencil & Eraser

5 analytic questions from lectures 02-06

 

 

 

 

Exercise-7

Spectrogram modification

 

 

 

 

Exercise-8

Spectrogram modification (2)

 

 

 

 

 

Exercise-9

FIR filter design

 

 

Exercise-10

Noise

 

Exercise-11

Linear predictive coding (LPC)

 

 

Exercise-12

Pitch

 

 

Exercise-13

Cepstrum

 

 

 


Note that the average values are calculated after excluding the two lowest exercise points!

Lab. Work Grading: