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Scheda Riassuntiva
Anno Accademico 2018/2019
Scuola Scuola di Ingegneria Industriale e dell'Informazione
Insegnamento 091032 - AUDIO AND VIDEO SIGNALS
  • 091030 - AUDIO SIGNALS
Docente Bestagini Paolo
Cfu 5.00 Tipo insegnamento Modulo Di Corso Strutturato

Corso di Studi Codice Piano di Studio preventivamente approvato Da (compreso) A (escluso) Insegnamento
Ing Ind - Inf (Mag.)(ord. 270) - MI (474) TELECOMMUNICATION ENGINEERING - INGEGNERIA DELLE TELECOMUNICAZIONI*AZZZZ091032 - AUDIO AND VIDEO SIGNALS
091041 - AUDIO SIGNALS
Ing Ind - Inf (Mag.)(ord. 270) - MI (487) MATHEMATICAL ENGINEERING - INGEGNERIA MATEMATICA*AZZZZ095978 - AUDIO AND VIDEO SIGNALS

Obiettivi dell'insegnamento

The goal of the course is to provide students with advanced audio signal processing skills and knowledge. In this course we first present the fundamental tools for analyzing, synthesizing and processing sounds (voice, music, acoustic signals). We then show how to use such tools for developing a wide range of applications, ranging from music information retrieval to acoustic array processing. Topics are treated both theoretically and practically.


Risultati di apprendimento attesi

Dublin Descriptors

Expected learning outcomes

Knowledge and understanding

Students will learn how to:

·       Study the interaction between audio signals and the human perception system

·       Process a digital audio signal properly taking care of resolution limitations in terms of time and frequency

·       Make use of audio signals for spatial analysis applications

·       Extract features and descriptors from audio signals useful for acoustic characterization as well as for information retrieval scenarios

Applying knowledge and understanding

Students will be able to:

·       Implement advanced audio processing algorithms (e.g., denoising, dereverberation, audio effects, etc.)

Making judgements

Given a relatively complex problem, students will be able to:

·       Analyze and understand the goals, assumptions and requirements associated with the problem

·       Define the algorithmic procedure to solve the problem (e.g., choice of a suitable solution, parameters estimation and tuning, etc.)

Communication

Students will learn to:

·       Write a detailed description of audio analysis systems

·       Present their work abstracting from the selected implementation


Argomenti trattati
  • Fundamentals
    • physiology of the hearing system and psycho-perception of sound
    • elements of acoustics
    • basic audio analysis: time-frequency analysis with Short-Time Fourier Transform or filterbanks
    • sound processing tools: filtering, nonlinear processing, auralization filters
    • adaptive filtering: Wiener-Hopf filter, steepest descent, LMS
    • space-time (array) processing: microphone arrays, beamforming
    • feature extraction and analysis
    • overview of sound synthesis tools: modulated delay lines, tunable delay lines, digital waveguides
  • Applications
    • harmonic analysis: pitch tracking, vocoder, envelope tracking
    • sound modification: time warping (resampling), time and pitch scaling (tonal and rhythmic corrector)
    • modulated delay lines and sound effects for musical applications: flanger, chorus, distortions, etc.
    • sound reverberation: perceptual methods, physics-inspired methods, geometric methods (acoustic ray and beam tracing)
    • music information retrieval: feature-based analysis and classification of musical excerpts, playlist generation, mood extraction, etc.
    • adaptive sound processing and applications: echo cancellation, noise reduction, dereverberation, etc.
    • array processing: beamforming, acoustic source localization and extraction (demixing), acoustic room compensation 

Prerequisiti

Students are required to know the basic principles of digital signal processing.


Modalità di valutazione

The assessment will be based on a written exam at the end of the course. The written exam consists of numerical exercises and theoretical questions. This will assign up to 31 points. Students achieving a score greater than or equal to 28 can develop an optional project. The project must be planned with the teacher, and it can provide up to 4 additional points. 30 cum laude will be assigned when the total score is higher than 31.

Type of assessment

Description

Dublin descriptors

Written test

Solution of numerical problems

·       Time and frequency audio resolution

·       Wiener filtering estimation

·       Microphone arrays for direction of arrival estimation

 

Exercises focusing on design aspects

·       Optiaml design of windowing solution for audio signal processing

·       Design of acoustic restoration systems

 

Theoretical questions on all course topics with open answer

·       Elements of acoustics and psychoacoustics

·       Sound analysis and synthesis tools

·       Audio effects and interpolated delay lines

·       Acoustic restoration and reverberation

·       Feature extraction and classification

·       Microphone arrays

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Bibliografia
Risorsa bibliografica facoltativaLecture notes and slides https://beep.metid.polimi.it/

Forme didattiche
Tipo Forma Didattica Ore di attività svolte in aula
(hh:mm)
Ore di studio autonome
(hh:mm)
Lezione
30:00
45:00
Esercitazione
20:00
30:00
Laboratorio Informatico
0:00
0:00
Laboratorio Sperimentale
0:00
0:00
Laboratorio Di Progetto
0:00
0:00
Totale 50:00 75:00

Informazioni in lingua inglese a supporto dell'internazionalizzazione
Insegnamento erogato in lingua Inglese
Disponibilità di materiale didattico/slides in lingua inglese
Disponibilità di libri di testo/bibliografia in lingua inglese
Possibilità di sostenere l'esame in lingua inglese
Disponibilità di supporto didattico in lingua inglese
schedaincarico v. 1.6.1 / 1.6.1
Area Servizi ICT
27/01/2020