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.
提供方
庞佩乌·法布拉·大学
斯坦福大学
音乐应用的音频信号处理
庞佩乌·法布拉·大学
課程信息
69,279 次近期查看
學生職業成果
67%
通過此課程獲得實實在在的工作福利
您將獲得的技能
Digital Signal ProcessingSignal ProcessingPython ProgrammingFft Algorithms
學生職業成果
67%
通過此課程獲得實實在在的工作福利
100% 在線
立即開始，按照自己的計劃學習。
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中級
完成時間大約為53 小時
建議：10 weeks of study, 8 hours/week
英語（English）
字幕：英語（English）
教學大綱 - 您將從這門課程中學到什麼
完成時間為 6 小時
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.
完成時間為 6 小時
11 個視頻 （總計 126 分鐘）, 1 個閱讀材料, 2 個測驗
11 個視頻
Teaser3分鐘
Welcome4分鐘
Introduction to Audio Signal Processing13分鐘
Course outline10分鐘
Basic mathematics16分鐘
Introduction to Audacity9分鐘
Introduction to SonicVisualizer10分鐘
Introduction to sms-tools17分鐘
Introduction to Python11分鐘
Python and sounds13分鐘
sms-tools software14分鐘
1 個閱讀材料
Advanced readings and videos10分鐘
1 個練習
Basics20分鐘
完成時間為 5 小時
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.
完成時間為 5 小時
6 個視頻 （總計 78 分鐘）, 1 個閱讀材料, 2 個測驗
1 個閱讀材料
Advanced readings and videos10分鐘
1 個練習
DFT20分鐘
完成時間為 5 小時
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.
完成時間為 5 小時
7 個視頻 （總計 99 分鐘）, 1 個閱讀材料, 2 個測驗
7 個視頻
Fourier properties 213分鐘
Periodic signals11分鐘
Complex sounds9分鐘
Spectrum13分鐘
Fourier properties23分鐘
dftModel13分鐘
1 個閱讀材料
Advanced readings and videos10分鐘
1 個練習
Fourier properties20分鐘
完成時間為 5 小時
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.
完成時間為 5 小時
6 個視頻 （總計 90 分鐘）, 1 個閱讀材料, 2 個測驗
1 個閱讀材料
Advanced readings and videos10分鐘
1 個練習
Short-time Fourier transform20分鐘
審閱
4.8
來自音乐应用的音频信号处理的熱門評論
由 LN 提供Dec 3, 2016
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!
由 EO 提供Dec 8, 2019
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.
由 HZ 提供Jan 20, 2017
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.
由 DA 提供Mar 6, 2019
Assignments are easily doable without any application of real analysis skills. You guys should actually ask us to build certain parts of your models so that we achieve that level of skill.
由 TB 提供Mar 7, 2018
Good lectures with a focus on practical applications. Good introduction to how signal processing can be used for musical analysis, and more specifically how to use the Essentia library
由 DA 提供Jun 6, 2017
Excellent material for an interesting subject. The video lectures are very good. The course does need some updates for Python3 and associated libraries to stay current.
由 FR 提供Dec 3, 2016
Very well explained and organized course material. The classes are also very detailed and special emphasis is put on illustrating every concept with example plots.
由 PS 提供Jun 4, 2017
Excellent course, for me this was pitched at just the right level to be interesting and also challenging. Everything was well explained and well structured.
由 AA 提供Mar 4, 2017
good course . If there will any Speech recognition course it will useful > Hope Coursera will start speech recognition course in future .
由 GI 提供Jul 10, 2019
Thank you kindly! The course is quite useful. I understood not only mathematics of Fourier Transform, but also the meaning of each step.
由 ME 提供Mar 5, 2018
It's a wonderful course when you can begin in the world of Digital Audio Processing. Very recommended! Thank you very much!
由 UD 提供Dec 17, 2016
I have just finished the week three and I'm enjoying every part of the course. Thank you, thank you and thank you again.
提供方
庞佩乌·法布拉·大学
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.
斯坦福大学
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.
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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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