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new notebooks with placeholders. work in progress

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README.md
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Appendix
--------
This information may not be up to date. Proceed at your own risk.
### Install Vagrant
We use [Vagrant](http://vagrantup.com) 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.
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about.html
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<p>This material is used during the annual Summer Workshop on Music Information Retrieval at CCRMA, Stanford University. <a href="https://ccrma.stanford.edu/workshops/music-information-retrieval-mir">Click here for workshop description and registration</a>.</p>
<p>This site is maintained by <a href="https://stevetjoa.com">Steve Tjoa</a>. For questions, please email <a href="mailto:steve@stevetjoa.com">steve@stevetjoa.com</a>. Do you have any feedback? Did you find errors or typos? Are you a teacher or researcher and would like to collaborate? Please let me know.</p>
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<h2 id="About-Fundamentals-of-Music-Processing">About <em>Fundamentals of Music Processing</em><a class="anchor-link" href="#About-Fundamentals-of-Music-Processing">&#182;</a></h2>
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<p>The book <a href="https://www.audiolabs-erlangen.de/fau/professor/mueller/bookFMP"><em>Fundamentals of Music Processing</em></a> (FMP) is a textbook by <a href="https://www.audiolabs-erlangen.de/fau/professor/mueller">Meinard Müller</a>, a well-known and prolific researcher in MIR, and published by Springer in 2015.</p>
<p>For many years, the field of music information retrieval has suffered from a lack of consolidated texts which unify its many disparate topics. Until now, students and researchers have had to learn about MIR mostly by reading the original research papers -- a daunting task. FMP is perhaps the best attempt to address this issue. It is a self-contained textbook which covers many MIR tasks such as feature extraction, audio-to-score alignment, musical form and structure, chord recognition, beat tracking, fingerprinting, and source separation.</p>
<p>We are integrating content from FMP into musicinformationretrieval.com in 2016.</p>
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about.ipynb
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"This site is maintained by [Steve Tjoa](https://stevetjoa.com). For questions, please email [steve@stevetjoa.com](mailto:steve@stevetjoa.com). Do you have any feedback? Did you find errors or typos? Are you a teacher or researcher and would like to collaborate? Please let me know."
]
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"metadata": {},
"source": [
"## About *Fundamentals of Music Processing*"
]
},
{
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"metadata": {
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"source": [
"The book [*Fundamentals of Music Processing*](https://www.audiolabs-erlangen.de/fau/professor/mueller/bookFMP) (FMP) is a textbook by [Meinard Müller](https://www.audiolabs-erlangen.de/fau/professor/mueller), a well-known and prolific researcher in MIR, and published by Springer in 2015.\n",
"\n",
"For many years, the field of music information retrieval has suffered from a lack of consolidated texts which unify its many disparate topics. Until now, students and researchers have had to learn about MIR mostly by reading the original research papers -- a daunting task. FMP is perhaps the best attempt to address this issue. It is a self-contained textbook which covers many MIR tasks such as feature extraction, audio-to-score alignment, musical form and structure, chord recognition, beat tracking, fingerprinting, and source separation.\n",
"\n",
"We are integrating content from FMP into musicinformationretrieval.com in 2016."
]
},
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"name": "python",
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"version": "2.7.11"
"version": "2.7.10"
}
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index.html
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index.ipynb
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"cell_type": "markdown",
"metadata": {},
"source": [
"1. [About This Site](about.html)\n",
"1. [About This Site](about.html) ([ipynb](about.ipynb))\n",
"1. [What is MIR?](why_mir.html)\n",
"1. [Python Basics](python_basics.html)\n",
"1. [Getting Good at IPython](get_good_at_ipython.html) ([ipynb](get_good_at_ipython.ipynb))\n",
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"1. [NumPy and SciPy Basics](numpy_basics.html) ([ipynb](numpy_basics.ipynb))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Chapter 1: Music Representations"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"1. [Sheet Music Representations](sheet_music_representations.html) ([ipynb](sheet_music_representations.ipynb))\n",
"1. [Symbolic Representations](symbolic_representations.html) ([ipynb](symbolic_representations.ipynb))\n",
"1. [Audio Representation](audio_representation.html) ([ipynb](audio_representation.ipynb))"
]
},
{
"cell_type": "markdown",
"metadata": {},
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"source": [
"1. [Overview of a Basic MIR System](basic_mir.html) ([ipynb](basic_mir.ipynb))\n",
"1. [Signal Representations](signal_representations.html) ([ipynb](signal_representations.ipynb))\n",
"1. [Onset Detection](onset_detection.html) ([ipynb](onset_detection.ipynb))\n",
"1. [Beat Tracking](beat_tracking.html) ([ipynb](beat_tracking.ipynb))\n",
"1. [Tempo Estimation](tempo_estimation.html) ([ipynb](tempo_estimation.ipynb))\n",
"1. [Exercise: Understanding Audio Features through Sonification](feature_sonification.html) ([ipynb](feature_sonification.ipynb))"
]
},
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"cell_type": "markdown",
"metadata": {},
"source": [
"## Chapter 2: Feature Extraction"
"## Chapter 2: Fourier Analysis of Signals"
]
},
{
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"1. [Basic Feature Extraction](basic_feature_extraction.html) ([ipynb](basic_feature_extraction.ipynb))\n",
"1. [Zero Crossing Rate](zcr.html) ([ipynb](zcr.ipynb))\n",
"1. [Spectral Features](spectral_features.html) ([ipynb](spectral_features.ipynb))\n",
"1. [Mel-Frequency Cepstral Coefficients](mfcc.html) ([ipynb](mfcc.ipynb))\n",
"1. [Pitch Transcription Exercise](pitch_transcription_exercise.html) ([ipynb](pitch_transcription_exercise.ipynb))"
]
},
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"cell_type": "markdown",
"metadata": {},
"source": [
"## Chapter 3: Classification"
"## Chapter 2.5: Classification"
]
},
{
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"cell_type": "markdown",
"metadata": {},
"source": [
"## Chapter 4: Matrix Factorization"
"## Chapter 3: Music Synchronization"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"1. [Principal Component Analysis](pca.html) ([ipynb](pca.ipynb))\n",
"1. [Nonnegative Matrix Factorization](nmf.html) ([ipynb](nmf.ipynb))\n",
"1. [Harmonic-Percussive Source Separation](hpss.html) ([ipynb](hpss.ipynb))\n",
"1. [Exercise: Source Separation using NMF](nmf_source_separation.html) ([ipynb](nmf_source_separation.ipynb))\n",
"1. [Classification of Separated Signals](notebooks/classify_separated_signals.ipynb)\n"
"## Chapter 4: Music Structure Analysis"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"1. [Mel-Frequency Cepstral Coefficients](mfcc.html) ([ipynb](mfcc.ipynb))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Chapter 5: Chord Recognition"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"1. [Tonal Descriptors: Pitch and Chroma](notebooks/tonal.ipynb)\n",
"\n",
"\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Chapter 6: Tempo and Beat Tracking"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"1. [Onset Detection](onset_detection.html) ([ipynb](onset_detection.ipynb))\n",
"1. [Beat Tracking](beat_tracking.html) ([ipynb](beat_tracking.ipynb))\n",
"1. [Tempo Estimation](tempo_estimation.html) ([ipynb](tempo_estimation.ipynb))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Chapter 5: Music Fingerprinting"
"## Chapter 7: Content-Based Audio Retrieval"
]
},
{
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"cell_type": "markdown",
"metadata": {},
"source": [
"## Appendix"
"## Chapter 8: Musically Informed Audio Decomposition"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"1. [Segmentation](segmentation.html) ([ipynb](segmentation.ipynb))\n",
"1. [Beat Tracking in Essentia](beat_tracking_essentia.html) ([ipynb](beat_tracking_essentia.ipynb))\n",
"1. [Spectral Features in Essentia](spectral_features_essentia.html) ([ipynb](spectral_features_essentia.ipynb))\n",
"1. [Feature Extraction in Essentia](feature_extraction_essentia.html) ([ipynb](feature_extraction_essentia.ipynb))"
"1. [Principal Component Analysis](pca.html) ([ipynb](pca.ipynb))\n",
"1. [Nonnegative Matrix Factorization](nmf.html) ([ipynb](nmf.ipynb))\n",
"1. [Harmonic-Percussive Source Separation](hpss.html) ([ipynb](hpss.ipynb))\n",
"1. [Exercise: Source Separation using NMF](nmf_source_separation.html) ([ipynb](nmf_source_separation.ipynb))\n",
"1. [Classification of Separated Signals](notebooks/classify_separated_signals.ipynb)\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## More (work in progress)"
"## Appendix"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"1. [Tonal Descriptors: Pitch and Chroma](notebooks/tonal.ipynb)\n",
"\n",
"\n"
"1. [Segmentation](segmentation.html) ([ipynb](segmentation.ipynb))\n",
"1. [Beat Tracking in Essentia](beat_tracking_essentia.html) ([ipynb](beat_tracking_essentia.ipynb))\n",
"1. [Spectral Features in Essentia](spectral_features_essentia.html) ([ipynb](spectral_features_essentia.ipynb))\n",
"1. [Feature Extraction in Essentia](feature_extraction_essentia.html) ([ipynb](feature_extraction_essentia.ipynb))"
]
}
],
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