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Risorse bibliografiche
Risorsa bibliografica obbligatoria
Risorsa bibliografica facoltativa
Scheda Riassuntiva
Anno Accademico 2019/2020
Scuola Scuola di Ingegneria Industriale e dell'Informazione
Insegnamento 052820 - SOUND ANALYSIS, SYNTHESIS AND PROCESSING
  • 052818 - SOUND ANALYSIS, SYNTHESIS AND PROCESSING MODULE 1: DIGITAL AUDIO ANALYSIS AND PROCESSING
Docente Sarti Augusto
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 (263) MUSIC AND ACOUSTIC ENGINEERING*AZZZZ054275 - SOUND ANALYSIS, SYNTHESIS AND PROCESSING MODULE 1: DIGITAL AUDIO ANALYSIS AND PROCESSING
052820 - SOUND ANALYSIS, SYNTHESIS AND PROCESSING
Ing Ind - Inf (Mag.)(ord. 270) - MI (474) TELECOMMUNICATION ENGINEERING - INGEGNERIA DELLE TELECOMUNICAZIONI*AZZZZ088967 - SOUND ANALYSIS, SYNTHESIS AND PROCESSING
Ing Ind - Inf (Mag.)(ord. 270) - MI (481) COMPUTER SCIENCE AND ENGINEERING - INGEGNERIA INFORMATICA*AZZZZ088967 - SOUND ANALYSIS, SYNTHESIS AND PROCESSING

Obiettivi dell'insegnamento

This module is part of a course that offers a comprehensive collection of fundamentals tools for for audio and acoustic signal analysis and processing, as well as synthesis and rendering. This specific module focuses on tools for audio analysis and processing.

A wide range of applications will be covered, including time and pitch scaling, sound restoration and improvement, music information retrieval, sound classification, acoustic source localization and tracking, adaptive processing, etc.


Risultati di apprendimento attesi

The student will acquire the fundamental tools of audio and acoustic signal processing and will acquire the ability to use such tools for applications of audio and acoustic signal analysis, synthesis, processing, improvement and restoration.


Argomenti trattati

Module 1 -  Digital audio analysis and processing

 

In this first part we cover relevan applications of digital audio signal processing for various applications, ranging from audio restoration to adaptive audio processing and array processing. After an introduction to acoustics and psycho-acoustics, we will cover:

 

  • Sinusoidal modeling - resolution of periodic signals and windowing, spectral interpolation, sinusoidal peak tracking and continuation. Speech modeling (synthesis through analysis). Channel and phase vocoder design.
  • Statistical audio processing - Wiener filtering: problem statement, orthogonality principle, Wiener-Hopf eqs., error performance surface. Typical applications of Wiener filtering: echo cancellation, noise cancellation, etc. Linear Prediction Coding: problem statement and application. Kalman filtering: problem statement, Bayesian model. Equalization: typical DSP structures for equalization.
  • Audio restoration - noise modeling, removal of typical audio artifacts: clicks, crackles, background noise, hissing noise, wow and flutter, nonlinear distortions. Statistical filtering and equalization
  • Fundamentals of microphone array signal processing - data model, non parametric methods (beamforming and Minimum Variance Distortionless Beamforming). Parametric methods: MUSIC.
  • Feature extraction and analysis: low-level descriptors (time-domain, spectral and timbral features), sound classification and similarity (dimensionality reduction, PCA classification methods

 

 


Prerequisiti

In order to best approach this course, the student should have a reasonable grasp of linear algebra; Fourier analysis and signal decomposition; signal theory; and probability theory.


Modalità di valutazione

The student is required to do a written test, whose grade can be integrated with a project. If the student decides not to do the project for a course module, the written test grade will be clipped to 27/30, otherwise the "unclipped" grade will be averaged with the project grade.
The project must be preliminarily negotiated with a course instructor and can be either a software application or a research paper. Projects can be done in collaboration with other students.


Bibliografia
Risorsa bibliografica facoltativaMark Kahrs, Karlheinz Brandenburg, Applications of Digital Signal Processing to Audio and Acoustics, Editore: Springer-Verlag, Anno edizione: 1998, ISBN: 9781475783865
Risorsa bibliografica facoltativaSimon Haykin, ADAPTIVE FILTER THEORY, Editore: Pearson, Anno edizione: 2014, ISBN: 9780273764083
Risorsa bibliografica facoltativaSimon J. Godsill, Peter J. W. Rayner, Digital Audio Restoration: A Statistical Model Based Approach, Editore: Springer-Verlag, Anno edizione: 1998, ISBN: 9783540762225
Risorsa bibliografica facoltativaPetre Stoica, Randolph Moses, Introduction to Spectral Analysis, Editore: Prentice Hall, Anno edizione: 1997, ISBN: 9780132584197

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. 1.6.4 / 1.6.4
Area Servizi ICT
10/07/2020