stanford-mir

Instructional material for the Music Information Retrieval Workshop at CCRMA, Stanford University, 2014-15.

How to Use This Repo

This repo contains a bunch of IPython notebooks related to music information retrieval.

If you're a visitor, browse a read-only version of this repo at musicinformationretrieval.com.

If you're a workshop participant, follow the steps below to get started with Git and IPython.

Install Git

Git is a version control system. You will use Git to retrieve the latest version of our IPython notebooks and to track changes that you make to these notebooks.

Download Git, and install it on your local machine.

Clone this repo onto your local machine:

macbook:~$ git clone https://github.com/stevetjoa/stanford-mir

Start IPython

A majority of our instruction and laboratory work will occur inside the IPython notebook. You can think of the IPython notebook like the Mathematica or Matlab desktop, except it's in Python and it runs inside your web browser.

Start the IPython notebook server:
```
stanford-mir:~$ ipython notebook
```
On your host machine, visit http://localhost:8888.
Open the notebook index.ipynb, or click on any .ipynb file to open it.

Congratulations, you are now running an IPython notebook, and you can get started with the workshop material.

Contributions

Your contributions are very welcome! You can contribute in two ways:

Submit an issue. Click on "Issues" in the right navigation bar, then "New Issue". Issues can include Python bugs, spelling mistakes, broken links, requests for new content, and more. For a prioritized list of open issues awaiting contribution, click on the blue "Ready" button above.
Submit changes to source code or documentation. Fork this repo, make edits, then submit a pull request.

Appendix

Install Vagrant

We use Vagrant to create a local virtual machine running Ubuntu 12.04. Vagrant ensures that every person has exactly the same development environment with the same installed packages.

Vagrant is available for all major operating systems, including Windows, Mac OS X, and Linux. It's a breeze to install.

Install VirtualBox and Vagrant.
Create a new virtual machine using our customized Vagrant box built upon Ubuntu 12.04 64-bit.
```
macbook:~/stanford-mir$ vagrant up
```
If this is your first time running vagrant up, this step may take five minutes to download the Vagrant box.
Finally, login to the new virtual machine:
```
macbook:~/stanford-mir$ vagrant ssh
```
This step logs you in to Ubuntu locally as user vagrant with default password vagrant.

Note: do not upgrade the virtual machine to Ubuntu 14.04 when prompted.

Note: outdated versions of Mac OS X may yield problems with vagrant ssh. To avoid such problems, please upgrade (for free) to the latest version of Mac OS X.

Troubleshooting Vagrant

Problem: When on a Windows host machine, vagrant ssh results in a timeout error: ssh_exchange_identification: read: Connection reset by peer.

Solution: Go into the BIOS, and make sure that Hardware Virtualization is enabled. For details, see this answer on Stack Overflow.
Problem: The folder stanford-mir on the guest machine is empty.

Solution: Vagrant probably failed to sync folders between the host and the guest machines. Try vagrant provision or vagrant reload from the host machine.

Name		Name	Last commit message	Last commit date
Latest commit History 173 Commits
notebooks		notebooks
sources		sources
stanford_mir		stanford_mir
.gitignore		.gitignore
CNAME		CNAME
LICENSE		LICENSE
README.md		README.md
Table_of_Contents.ipynb		Table_of_Contents.ipynb
Vagrantfile		Vagrantfile
about.html		about.html
about.ipynb		about.ipynb
basic_feature_extraction.html		basic_feature_extraction.html
basic_feature_extraction.ipynb		basic_feature_extraction.ipynb
basic_mir.html		basic_mir.html
basic_mir.ipynb		basic_mir.ipynb
basic_mir.slides.html		basic_mir.slides.html
beat_tracking.html		beat_tracking.html
beat_tracking.ipynb		beat_tracking.ipynb
beat_tracking.slides.html		beat_tracking.slides.html
beat_tracking_essentia.html		beat_tracking_essentia.html
beat_tracking_essentia.ipynb		beat_tracking_essentia.ipynb
classify_separated_signals.ipynb		classify_separated_signals.ipynb
cross_validation.html		cross_validation.html
cross_validation.ipynb		cross_validation.ipynb
custom.css		custom.css
evaluation.html		evaluation.html
evaluation.ipynb		evaluation.ipynb
feature_extraction_essentia.ipynb		feature_extraction_essentia.ipynb
feature_sonification.html		feature_sonification.html
feature_sonification.ipynb		feature_sonification.ipynb
get_good_at_ipython.html		get_good_at_ipython.html
get_good_at_ipython.ipynb		get_good_at_ipython.ipynb
get_good_at_ipython.slides.html		get_good_at_ipython.slides.html
hpss.html		hpss.html
hpss.ipynb		hpss.ipynb
index.html		index.html
index.ipynb		index.ipynb
ipython_audio.html		ipython_audio.html
ipython_audio.ipynb		ipython_audio.ipynb
ipython_audio.slides.html		ipython_audio.slides.html
kmeans.html		kmeans.html
kmeans.ipynb		kmeans.ipynb
kmeans_instrument_classification.html		kmeans_instrument_classification.html
kmeans_instrument_classification.ipynb		kmeans_instrument_classification.ipynb
knn.html		knn.html
knn.ipynb		knn.ipynb
knn_instrument_classification.html		knn_instrument_classification.html
knn_instrument_classification.ipynb		knn_instrument_classification.ipynb
lsh_fingerprinting.html		lsh_fingerprinting.html
lsh_fingerprinting.ipynb		lsh_fingerprinting.ipynb
mfcc.html		mfcc.html
mfcc.ipynb		mfcc.ipynb
mfcc.slides.html		mfcc.slides.html
nmf.html		nmf.html
nmf.ipynb		nmf.ipynb
nmf_source_separation.html		nmf_source_separation.html
nmf_source_separation.ipynb		nmf_source_separation.ipynb
numpy_basics.html		numpy_basics.html
numpy_basics.ipynb		numpy_basics.ipynb
numpy_basics.slides.html		numpy_basics.slides.html
onset_detection.html		onset_detection.html
onset_detection.ipynb		onset_detection.ipynb
onset_detection.slides.html		onset_detection.slides.html
pca.html		pca.html
pca.ipynb		pca.ipynb
pitch_transcription_answer.ipynb		pitch_transcription_answer.ipynb
pitch_transcription_exercise.html		pitch_transcription_exercise.html
pitch_transcription_exercise.ipynb		pitch_transcription_exercise.ipynb
python_basics.html		python_basics.html
python_basics.ipynb		python_basics.ipynb
segmentation.html		segmentation.html
segmentation.ipynb		segmentation.ipynb
signal_representations.html		signal_representations.html
signal_representations.ipynb		signal_representations.ipynb
signal_representations.slides.html		signal_representations.slides.html
spectral_features.html		spectral_features.html
spectral_features.ipynb		spectral_features.ipynb
spectral_features_essentia.html		spectral_features_essentia.html
spectral_features_essentia.ipynb		spectral_features_essentia.ipynb
tempo_estimation.html		tempo_estimation.html
tempo_estimation.ipynb		tempo_estimation.ipynb
tonal.ipynb		tonal.ipynb
why_mir.html		why_mir.html
why_mir.ipynb		why_mir.ipynb
why_mir.slides.html		why_mir.slides.html
zcr.html		zcr.html
zcr.ipynb		zcr.ipynb

License

RichardYang40148/stanford-mir

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