Difference between revisions of "MIR workshop 2008 notes"
From CCRMA Wiki
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= Real-world applications = | = Real-world applications = | ||
| + | == Audio Segmentation == | ||
| + | [http://www.ifs.tuwien.ac.at/mir/audiosegmentation.html Automatic Audio Segmentation: Segment Boundary and Structure Detection in Popular Music] | ||
| + | |||
== Audio Fingerprinting == | == Audio Fingerprinting == | ||
* [http://ieeexplore.ieee.org/iel5/8561/27103/01203274.pdf?tp=&isnumber=&arnumber=1203274 P. Cano, E. Batlle, T. Kalker, and J. Haitsma, “A review of algorithms for audio fingerprinting,” in IEEE International Workshop on Multimedia Signal Processing (MMSP), pp. 169 – 173, December 2002. 4 pages.] | * [http://ieeexplore.ieee.org/iel5/8561/27103/01203274.pdf?tp=&isnumber=&arnumber=1203274 P. Cano, E. Batlle, T. Kalker, and J. Haitsma, “A review of algorithms for audio fingerprinting,” in IEEE International Workshop on Multimedia Signal Processing (MMSP), pp. 169 – 173, December 2002. 4 pages.] | ||
Revision as of 15:28, 14 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.
Contents
- 1 Timing and Segmentation
- 2 Feature Extraction
- 3 Analysis / Decision Making
- 4 Model / Data Preparation Techniques
- 5 Evaluation Methodology
- 6 Real-world applications
- 7 Getting Involved in the MIR Community
Timing and Segmentation
Onset Detection
Papers
Code
Beat Extraction
Papers
Code
Tempo Extraction
Papers
- Tempo and beat analysis of acoustic musical signals
- Determination of the meter of musical scores by autocorrelation
- Tempo and beat analysis of acoustic musical signals
- An Audio-based Real-time Beat Tracking System for Music With or Without Drum-sounds
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
- The interactive Matlab SVM Demo that I demonstrated on Lecture 5 comes from here
- A nice SVM java applet to demo the concepts
- Andrew Moore's SVM Powerpoint Lecture
- User community of SVM enthusiasts
- A practical guide to SVM classification
- SVM Practical (How to get good results without cheating)
- One-class SVM posting
Code
Clustering and probability density models
Density distance measures (centroid distance, EMD, KL-divergence, etc)
k-Means
Clustering
GMM
- Simple review of probability with introduction of Bayes Rules
- Good description of conditional probabilities
- EM explained
- Expectation-Maximization Java Applet
- Lab featuring real-world GMM examples for singing detection
- Dan Ellis' Speech and Audio Processing Lectures
HMM
- High-level introduction to HMM
- “A tutorial on hidden markov models and selected applications in speech recognition” Lawrence Rabiner, Proc. IEEE, 77(2), Feb 1989.
- A self-directed introduction / lab for HMMs
- Matlab Introduction to HMM functions
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 Segmentation
Automatic Audio Segmentation: Segment Boundary and Structure Detection in Popular Music
Audio Fingerprinting
- P. Cano, E. Batlle, T. Kalker, and J. Haitsma, “A review of algorithms for audio fingerprinting,” in IEEE International Workshop on Multimedia Signal Processing (MMSP), pp. 169 – 173, December 2002. 4 pages.
- "On the comparison of audio fingerprints for extracting quality parameters of compressed audio"
- Finding Structure in Audio for Music Information Retrieval
