Difference between revisions of "MIR workshop 2008 notes"

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(HMM)
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* [http://www.comp.leeds.ac.uk/roger/HiddenMarkovModels/html_dev/main.html High-level introduction to HMM]
 
* [http://www.comp.leeds.ac.uk/roger/HiddenMarkovModels/html_dev/main.html High-level introduction to HMM]
 
* [http://www.ee.columbia.edu/dpwe/e6820/papers/Rabiner89-hmm.pdf “A tutorial on hidden markov models and selected applications in speech recognition”  Lawrence Rabiner, Proc. IEEE, 77(2), Feb 1989.]
 
* [http://www.ee.columbia.edu/dpwe/e6820/papers/Rabiner89-hmm.pdf “A tutorial on hidden markov models and selected applications in speech recognition”  Lawrence Rabiner, Proc. IEEE, 77(2), Feb 1989.]
 +
* [http://www.ee.columbia.edu/dpwe/e6820/matlab/epflhmm/labman2.pdf A self-directed introduction / lab for HMMs]
  
 
==  Nested classifier / Anchor-space / template-based systems ==  
 
==  Nested classifier / Anchor-space / template-based systems ==  

Revision as of 14:10, 1 August 2008

This page is intended to supplement the lecture material found in the class - providing extra tutorials, support, references for further reading, or demonstration code snippets for those interested in a given topic. Please contribute to this growing list of resources. Do you have a great explanation of how a technique works? Found a great Java applet that illustrates a concept? Discovered a great survey of the field for a particular area? Please add it for the benefit of future students. Thanks!

I encourage you to ADD links and sections - but please do not REMOVE headings or items from the page.

Timing and Segmentation

Onset Detection

Papers

Code

Beat Extraction

Papers

Code

Tempo Extraction

Papers

Code

Feature Extraction

Low Level Features

Zero Crossing, Temporal centroid, Log Attack time, Attack slope), Spectral features (Centroid, Flux, RMS, Rolloff, Flatness, Kurtosis, Brightness),Spectral bands, Log spectrogram

Chroma bins

MFCC

Auditory Toolbox (code and docs)

MPEG-7

Higher-level features

Key Estimation

Chord Estimation

Genre (genre, artist ID, similarity)

"Fingerprints"

Visualizing and Sonifying Feature data

Matt Hoffman's feature sonification work

Analysis / Decision Making

Classification

Heuristic Analysis

Distance measures (Euclidean, Manhattan, etc.)

k-NN

SVM / One-class SVM

Resources

Code

Clustering and probability density models

Density distance measures (centroid distance, EMD, KL-divergence, etc)

k-Means

Clustering

GMM

HMM

Nested classifier / Anchor-space / template-based systems

Model / Data Preparation Techniques

Data Preparation

PCA / LDA

Scaling data

Model organization

  • concept, design, data set construction and organization

Evaluation Methodology

Feature selection

Cross Validation

Information Retrieval metrics (precision, recall, F-Measure)

Real-world applications

Audio Fingerprinting

Drum Transcription

Audio Similarity

Music Recommendation / Playlisting