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Introduction to sound processing

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  • Lecturer: Henri BOUTIN (henri.boutin@sorbonne-universite.fr)
  • Course code: UM4RBI11-Son1
  • Student workload: 12h of lectures, 6h of tutorials, 10h of labs
  • Credits: 3 ECTS
  • Specialization tracks:
  • Semester offered: S1 S2 S3 S4
  • Language of instruction: French English
  • Targeted audience: Eng. Sc. department Other :
  • Localization : PMC Campus Other :

Course Overview

This course aims to train students in the analysis and processing of an audio signal in time and frequency. The teaching focuses on the analysis, modeling and coding of speech and music signals.

Mots-clés : Signal Processing, Audio Signal, Music, Speech, Time-Frequency Analysis, Short-Term Fourier Transform, Overlap Add Algorithm, Source-Filter Model, LPC (Linear Predicting Coding), Cepstre, Perception, Coding, Compression.

Prerequisites

Students should have previously acquired the following prerequisites to follow this course:

  • Analog signal processing: convolution, series and continuous-time Fourier transform;
  • Discrete signal processing: Discrete Signal Fourier Transform, Discrete Fourier Transform;

Intended Learning Outcomes

By the end of this course, students will be able to:

  1. Identify the characteristics of an audio signal in the time domain: periodicity / attacks / transients
  2. Identify the characteristics of an audio signal in the frequency domain: timbre, spectral centroid, etc.
  3. Master the theoretical tools of time-frequency analysis to make the link between these 2 types of characteristics: TF, TFSD, TFD and TFCT
  4. Knowing how to analyze and synthesize a speech signal with a Source-Filter model
  5. Distinguish between descriptors and parameters in speech signal models
  6. Know and understand how an audio signal coding system works
  7. Know how to optimize the encoding and compression, lossless or lossy, of an audio signal
  8. Know how to process a human audio signal, production and perception devices in humans
  9. Know how to analyze, characterize and model a musical signal using timbre descriptors
  10. Knowing how to identify a musical structure by processing similarity matrices
  11. Know how to evaluate the analysis algorithms implemented

Indicative Teaching Sequence and Methods

Week C/TD/TP* Content Preparation Learn.\ outc.
S1 C1 Production chain / acquisition / restitution / perception AUDIO AAV1-2 / 8
S2 C2 / TD1 Frequency analysis of a digital audio signal Review prerequisites: analog and discrete signal processing AAV1-3
S3 C3 / TP1 Time-frequency analysis of an audio signal Preparation TP1 AAV1-3 / 5 / 9
S4 C4 / TD2 Sound production and perception in humans AAV4-5 / 8 / 1-2
S5 C5 / TP2 Application to the encoding of an audio signal Preparation TP2 AAV6-7 / 1-2
S6 C6 / TP3 Automatic analysis of musical signals review C3 + TP3 preparation AAV9-11 / 3
S7 TD3 review C4 and C5 AAV4-5
S8 TP4 review C4 and C5 + preparation TP4 AAV6-8
S9 TP5 TP5 preparation AAV1-3 / 9
  • C/TD/TP respectively corresponds to lectures, tutorials and lab sessions.

Sequence of the unit

The UE takes place in 3 sequences:

  • Sequence 1: Time-frequency analysis of an audio signal (C1-3 + TD1/2 + TP1-3 + DC)

  • Sequence 2: Production and perception of sound in humans and application to the coding of an audio signal (C4/5 + TD3 + TP4)

  • Sequence 3: Automatic analysis of musical signals (C6 + TP5 + ER + Exam de TP)

Indicative Assessment of Intended Learning Outcomes (1st session)

Week Individ./group In-person/remote Type of exam Evaluated outcomes Scale %
S4 Individual In-person Written AAV 1-3 20%
S8 Individual In-person Written AAV 4-11 40%
S10 Individual In-person Practical AAV 1-3 / 6 - 9 40%

2nde session

Session Individ./group In-person/remote Type of exam Evaluated outcomes Scale %
2 Individual In-person Written AAV 1-11 60%
1 Individual In-person Practical AAV 1-3 / 6 - 9 40%

Bibliographic references

  • Blanchet \& Charbit, 2001, "Signaux et Images sous Matlab". Hermes Sciences.
  • Kahrs, 1998, "Applications of digital signal processing to audio and acoustics", Kluwer Academic Publishers.
  • Hartmann, 1996, "signal, sound and sensation", Springer-Verlag
  • Hayes, 1996, "Statistical Digital Signal Processing", John Wiley
  • Imai \& Abe, "Spectral Envelope Extraction by Improved Cepstral Method"

Logo SDI Date of generation of this unit description: 14/01/2026 Logo SDI