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http://recherche.ircam.fr/anasyn/peeters/ARTICLES/Peeters_2003_cuidadoaudiofeatures.pdf
G. Peeters A Large Set of Audio Features for Sound Description 2004 23/04/04 13/25 6 Spectral features 6.1 Spectral shape description 6.1.1 Spectral centroid (mpeg7:AudioSpectrumCentroid) DS.i_sc_v = ⋅ µ δ • = • = 6.1.2 Spectral spread (mpeg7:AudioSpectrumSpread) DS.i_ss_v = − ⋅ σ µ δ
A large set of audio features for sound description ...
https://www.researchgate.net/publication/200688649_A_large_set_of_audio_features_for_sound_description_similarity_and_classification_in_the_CUIDADO_project
Request PDF | On Jan 1, 2004, Geoffroy Peeters published A large set of audio features for sound description (similarity and classification) in the CUIDADO project | Find, read and cite all the ...
Audio features - w2.mat.ucsb.edu
https://w2.mat.ucsb.edu/240/E/static/notes/Audio_features.html
From: Peeters, G. (2004). A large set of audio features for sound description (similarity and classification) in the CUIDADO project (pp. 1–25).
CiteSeerX — Citation Query A large set of audio features ...
https://citeseerx.ist.psu.edu/showciting?cid=259635
A large set of audio features for sound description (similarity and classification) in the cuidado project (2004) by G Peeters Add To MetaCart. Tools. Sorted by: Results 1 - 10 of 200. Next 10 → Melody extraction from polyphonic music signals using pitch contour characteristics ...
A large set of audio features for sound description ...
https://www.bibsonomy.org/bibtex/2730f3af81ec228afe946a8f1e57810e5/zazi
A large set of audio features for sound description (similarity and classification) in the CUIDADO project. G. Peeters. Icram, (2004
When audio features reach machine learning
http://recherche.ircam.fr/anasyn/peeters/ARTICLES/Peeters_2015_ICML_AudioFeatures.pdf
was based on the extraction of a large set of audio features (Peeters,2004), automatic feature selection algorithm and generative classifiers (GMM). The system was single-label. The trained system was then integrated into MPO Online/ WMI music catalogue. The development of the system was done on a database of around 5000 tracks.
Audio Feature - an overview | ScienceDirect Topics
https://www.sciencedirect.com/topics/engineering/audio-feature
The authors review the most important recent feature extraction techniques for fingerprinting. Peeters [48] summarizes a large set of audio features. The author organizes the features among others in global and frame-based descriptions, spectral features, energy features, harmonic features, and perceptual features.
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