Informações sobre o curso

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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.

100% on-line

Comece imediatamente e aprenda em seu próprio cronograma.

Prazos flexíveis

Redefinir os prazos de acordo com sua programação.

Nível intermediário

Aprox. 53 horas para completar

Sugerido: 10 weeks of study, 8 hours/week...

Inglês

Legendas: Inglês

Habilidades que você terá

Digital Signal ProcessingSignal ProcessingPython ProgrammingFft Algorithms

100% on-line

Comece imediatamente e aprenda em seu próprio cronograma.

Prazos flexíveis

Redefinir os prazos de acordo com sua programação.

Nível intermediário

Aprox. 53 horas para completar

Sugerido: 10 weeks of study, 8 hours/week...

Inglês

Legendas: Inglês

Programa - O que você aprenderá com este curso

Semana

1

6 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 126 mín.), 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

2

5 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 78 mín.), 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

3

5 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 99 mín.), 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

4

5 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 90 mín.), 1 leitura, 2 testes

6 videos

STFT 117min

STFT 216min

Spectrogram10min

Analyzing a sound14min

Windows16min

STFT14min

1 leituras

Advanced readings and videos10min

1 exercício prático

Short-time Fourier transform20min

Semana

5

5 horas para concluir

Sinusoidal model

Sinusoidal model equation; sinewaves in a spectrum; sinewaves as spectral peaks; time-varying sinewaves in spectrogram; sinusoidal synthesis. Demonstration of the sinusoidal model interface of the sms-tools package and its use in the analysis and synthesis of sounds. Implementation of the detection of spectral peaks and of the sinusoidal synthesis using Python and presentation of the sineModel functions from the sms-tools package, explaining how to use them.

8 vídeos (Total 115 mín.), 1 leitura, 2 testes

8 videos

Sinusoidal model 115min

Sinusoidal model 213min

Sinusoidal model 317min

Sinusoidal model13min

Analyzing a sound12min

Peak detection14min

Sinusoidal synthesis12min

sineModel16min

1 leituras

Advance reading10min

1 exercício prático

Sinusoidal model20min

Semana

6

5 horas para concluir

Harmonic model

Harmonic model equation; sinusoids-partials-harmonics; polyphonic-monophonic signals; harmonic detection; f0-detection in time and frequency domains. Demonstrations of pitch detection algorithm, of the harmonic model interface of the sms-tools package and of its use in the analysis and synthesis of sounds. Implementation of the detection of the fundamental frequency in the frequency domain using the TWM algorithm in Python and presentation of the harmonicModel functions from the sms-tools package, explaining how to use them.

7 vídeos (Total 120 mín.), 1 leitura, 2 testes

7 videos

Harmonic model13min

F0 detection20min

Pitch detection14min

Harmonic model25min

Analyzing a sound14min

F0 detection16min

harmonicModel14min

1 leituras

Advanced readings10min

1 exercício prático

Harmonic model20min

Semana

7

5 horas para concluir

Sinusoidal plus residual model

Stochastic signals; stochastic model; stochastic approximation of sounds; sinusoidal/harmonic plus residual model; residual subtraction; sinusoidal/harmonic plus stochastic model; stochastic model of residual. Demonstrations of the stochastic model, harmonic plus residual, and harmonic plus stochastic interfaces of the sms-tools package and of its use in the analysis and synthesis of sounds. Presentation of the stochasticModel, hprModel and hpsModel functions implemented in the sms-tools package, explaining how to use them.

8 vídeos (Total 126 mín.), 1 leitura, 2 testes

8 videos

Stochastic model20min

Sinusoidal plus residual modeling16min

Stochastic model10min

Harmonic plus residual model14min

Harmonic plus stochastic model12min

stochasticModel17min

hprModel19min

hpsModel14min

1 leituras

Advanced readings10min

1 exercício prático

Sinusoidal plus residual model20min

Semana

8

5 horas para concluir

Sound transformations

Filtering and morphing using the short-time Fourier transform; frequency and time scaling using the sinusoidal model; frequency transformations using the harmonic plus residual model; time scaling and morphing using the harmonic plus stochastic model. Demonstrations of the various transformation interfaces of the sms-tools package and of Audacity. Presentation of the stftTransformations, sineTransformations and hpsTransformations functions implemented in the sms-tools package, explaining how to use them.

9 vídeos (Total 120 mín.), 1 leitura, 2 testes

9 videos

Sounds transformations 116min

Sounds transformations 216min

Morphing with STFT10min

Time scaling11min

Pitch changes12min

Morphing with HPS12min

stftTransformations18min

sineTransformations11min

hpsTransformations9min

1 leituras

Advanced readings10min

1 exercício prático

Sound transformations20min

Semana

9

5 horas para concluir

Sound and music description

Extraction of audio features using spectral analysis methods; describing sounds, sound collections, music recordings and music collections. Clustering and classification of sounds. Demonstration of various plugins from SonicVisualiser to describe sound and music signals and demonstration of some advance features of freesound.org. Presentation of Essentia, a C++ library for sound and music description, explaining how to use it from Python. Programming with the Freesound API in Python to download sound collections and to study them.

6 vídeos (Total 142 mín.), 2 testes

6 videos

Audio features30min

Sound and music description24min

Sound descriptors14min

Freesound20min

Intro to Essentia25min

Freesound API26min

1 exercício prático

Sound and music description20min

Semana

10

2 horas para concluir

Concluding topics

Audio signal processing beyond this course. Beyond audio signal processing. Review of the course topics. Where to learn more about the topics of this course. Presentation of MTG-UPF. Demonstration of Dunya, a web browser to explore several audio music collections, and of AcousticBrainz, a collaborative initiative to collect and share music data.

6 vídeos (Total 106 mín.), 1 leitura, 1 teste

6 videos

Beyond audio processing16min

Review12min

MTG-UPF18min

Goodbye17min

Dunya18min

AcousticBrainz22min

1 leituras

Advanced readings10min

1 exercício prático

Concluding topics20min

6 horas para concluir

Concluding topics: Lesson Choices

3 testes

Instrutores

Xavier Serra

Full Professor

Dept. of Information and Communication Technologies, UPF

Prof Julius O Smith, III

Professor of Music and (by courtesy) Electrical Engineering

CCRMA

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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Processamento de sinais de áudio para aplicativos musicais

100% on-line

Prazos flexíveis

Nível intermediário

Aprox. 53 horas para completar

Inglês

Habilidades que você terá

100% on-line

Prazos flexíveis

Nível intermediário

Aprox. 53 horas para completar

Inglês

Programa - O que você aprenderá com este curso

Introduction

Discrete Fourier transform

Fourier theorems

Short-time Fourier transform

Sinusoidal model

Harmonic model

Sinusoidal plus residual model

Sound transformations

Sound and music description

Concluding topics

Concluding topics: Lesson Choices

67%

Principais avaliações do Processamento de sinais de áudio para aplicativos musicais

Instrutores

Xavier Serra

Prof Julius O Smith, III

Sobre Universidade Pompeu Fabra de Barcelona

Sobre Universidade de Stanford

Perguntas Frequentes – FAQ