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.
提供：
ポンペウ・ファブラ大学（Universitat Pompeu Fabra of Barcelona）
スタンフォード大学（Stanford University）
Audio Signal Processing for Music Applications
ポンペウ・ファブラ大学（Universitat Pompeu Fabra of Barcelona）
このコースについて
47,250 最近の表示
Learner Career Outcomes
67%
コースが具体的なキャリアアップにつながった
習得するスキル
Digital Signal ProcessingSignal ProcessingPython ProgrammingFft Algorithms
Learner Career Outcomes
67%
コースが具体的なキャリアアップにつながった
100%オンライン
自分のスケジュールですぐに学習を始めてください。
柔軟性のある期限
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中級レベル
約53時間で修了
推奨：10 weeks of study, 8 hours/week
英語
字幕：英語
シラバス - 本コースの学習内容
6時間で修了
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.
6時間で修了
11件のビデオ （合計126分）, 1 reading, 2 quizzes
11件のビデオ
Teaser3 分
Welcome4 分
Introduction to Audio Signal Processing13 分
Course outline10 分
Basic mathematics16 分
Introduction to Audacity9 分
Introduction to SonicVisualizer10 分
Introduction to sms-tools17 分
Introduction to Python11 分
Python and sounds13 分
sms-tools software14 分
1件の学習用教材
Advanced readings and videos10 分
1の練習問題
Basics20 分
5時間で修了
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.
5時間で修了
6件のビデオ （合計78分）, 1 reading, 2 quizzes
1件の学習用教材
Advanced readings and videos10 分
1の練習問題
DFT20 分
5時間で修了
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.
5時間で修了
7件のビデオ （合計99分）, 1 reading, 2 quizzes
7件のビデオ
Fourier properties 213 分
Periodic signals11 分
Complex sounds9 分
Spectrum13 分
Fourier properties23 分
dftModel13 分
1件の学習用教材
Advanced readings and videos10 分
1の練習問題
Fourier properties20 分
5時間で修了
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.
5時間で修了
6件のビデオ （合計90分）, 1 reading, 2 quizzes
1件の学習用教材
Advanced readings and videos10 分
1の練習問題
Short-time Fourier transform20 分
4.8
62件のレビュー
Audio Signal Processing for Music Applications からの人気レビュー
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!
An absolutely awesome introduction to Audio Signal Processing. The additive introduction of new concepts is capable of teaching any beginner this topic which ordinarily is difficult to understand.
講師
Xavier Serra
Full ProfessorDept. of Information and Communication Technologies, UPF
Prof Julius O Smith, III
Professor of Music and (by courtesy) Electrical EngineeringCCRMA
ポンペウ・ファブラ大学（Universitat Pompeu Fabra of Barcelona）について
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.
スタンフォード大学（Stanford University）について
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.
よくある質問
いつ講座や課題にアクセスできるようになりますか？
修了証に登録すると、すべてのビデオ、テスト、およびプログラミング課題（該当する場合）にアクセスできます。ピアレビュー課題は、セッションが開始してからのみ、提出およびレビューできます。購入せずにコースを検討することを選択する場合、特定の課題にアクセスすることはできません。
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.
さらに質問がある場合は、受講者向けヘルプセンターにアクセスしてください。