In this course you will learn about audio signal processing methodologies that are specific for music and of use in real applications. We focus on the spectral processing techniques of relevance for the description and transformation of sounds, developing the basic theoretical and practical knowledge with which to analyze, synthesize, transform and describe audio signals in the context of music applications.
The course is based on open software and content. The demonstrations and programming exercises are done using Python under Ubuntu, and the references and materials for the course come from open online repositories. We are also distributing with open licenses the software and materials developed for the course.
Processamento de sinais de áudio para aplicativos musicais
oferecido por
Universidade Pompeu Fabra de Barcelona
Universidade de Stanford
Universidade Pompeu Fabra de Barcelona
Informações sobre o curso
4.8
197 classificações
Habilidades que você terá
Digital Signal ProcessingSignal ProcessingPython ProgrammingFft Algorithms
Programa - O que você aprenderá com este curso
Semana
16 horas para concluir
Introduction
Introduction to the course, to the field of Audio Signal Processing, and to the basic mathematics needed to start the course. Introductory demonstrations to some of the software applications and tools to be used. Introduction to Python and to the sms-tools package, the main programming tool for the course.
11 vídeos (total de (Total 126 mín.) min), 1 leitura, 2 testes
11 videos
Teaser3min
Welcome4min
Introduction to Audio Signal Processing13min
Course outline10min
Basic mathematics16min
Introduction to Audacity9min
Introduction to SonicVisualizer10min
Introduction to sms-tools17min
Introduction to Python11min
Python and sounds13min
sms-tools software14min
1 leituras
Advanced readings and videos10min
1 exercício prático
Basics20min
Semana
25 horas para concluir
Discrete Fourier transform
The Discrete Fourier Transform equation; complex exponentials; scalar product in the DFT; DFT of complex sinusoids; DFT of real sinusoids; and inverse-DFT. Demonstrations on how to analyze a sound using the DFT; introduction to Freesound.org. Generating sinusoids and implementing the DFT in Python.
6 vídeos (total de (Total 78 mín.) min), 1 leitura, 2 testes
6 videos
DFT 111min
DFT 216min
Analyzing a sound8min
Introduction to Freesound12min
Sinusoids14min
DFT15min
1 leituras
Advanced readings and videos10min
1 exercício prático
DFT20min
Semana
35 horas para concluir
Fourier theorems
Linearity, shift, symmetry, convolution; energy conservation and decibels; phase unwrapping; zero padding; Fast Fourier Transform and zero-phase windowing; and analysis/synthesis. Demonstration of the analysis of simple periodic signals and of complex sounds; demonstration of spectrum analysis tools. Implementing the computation of the spectrum of a sound fragment using Python and presentation of the dftModel functions implemented in the sms-tools package.
7 vídeos (total de (Total 99 mín.) min), 1 leitura, 2 testes
7 videos
Fourier properties 114min
Fourier properties 213min
Periodic signals11min
Complex sounds9min
Spectrum13min
Fourier properties23min
dftModel13min
1 leituras
Advanced readings and videos10min
1 exercício prático
Fourier properties20min
Semana
45 horas para concluir
Short-time Fourier transform
STFT equation; analysis window; FFT size and hop size; time-frequency compromise; inverse STFT. Demonstration of tools to compute the spectrogram of a sound and on how to analyze a sound using them. Implementation of the windowing of sounds using Python and presentation of the STFT functions from the sms-tools package, explaining how to use them.
6 vídeos (total de (Total 90 mín.) min), 1 leitura, 2 testes
1 leituras
Advanced readings and videos10min
1 exercício prático
Short-time Fourier transform20min
67%
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Melhores avaliações
Top class! Very well explained, good examples, excellent learning material, practical exercises, and lots and lots of room for further personal study! Well done guys, and especially Xavier! Cheers!
I learned a lot during this course. It took quite a lot of time and energy to complete it, but I'm glad I did. It is now much easier to follow the text of Richard Lyons' book. Highly recommended.
Instrutores
Xavier Serra
Full ProfessorDept. of Information and Communication Technologies, UPF
Prof Julius O Smith, III
Professor of Music and (by courtesy) Electrical EngineeringCCRMA
Sobre Universidade Pompeu Fabra de Barcelona
Pompeu Fabra University (UPF) is a modern public university, conveniently located in the centre of Barcelona (Spain) with the aim of providing top quality education and standing out as a research-based university. UPF is both a specialised university with a unique teaching model and a cutting-edge research institution. UPF places a strong emphasis on quality teaching, based on comprehensive education and student-centred learning, and innovation in the learning processes. UPF’s MOOCs are produced within this general goal.
Sobre Universidade de Stanford
The Leland Stanford Junior University, commonly referred to as Stanford University or Stanford, is an American private research university located in Stanford, California on an 8,180-acre (3,310 ha) campus near Palo Alto, California, United States.
Perguntas Frequentes – FAQ
Quando terei acesso às palestras e às tarefas?
Ao se inscrever para um Certificado, você terá acesso a todos os vídeos, testes e tarefas de programação (se aplicável). Tarefas avaliadas pelos colegas apenas podem ser enviadas e avaliadas após o início da sessão. Caso escolha explorar o curso sem adquiri-lo, talvez você não consiga acessar certas tarefas.
Can I take this course for free?
Yes, there is no fee in this course. You can follow the course, do the assignments, and obtain a final grade completely for free.
Can I pay to get a Course Certificate?
No, we do not offer this option.
What resources will I need for this class?
All the materials and tools for the class are available online under open licences.
Do I need to buy a textbook for the course?
No, it is self-contained.
How much programming background is needed for the course?
All the assignments start from some existing Python code that the student have to understand and modify. Some programming experience is necessary.
What is the coolest thing I'll learn if I take this class?
You will play around with sounds a lot, analysing them, transforming them, and making interesting new sounds.
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