Musical data mining for electronic music distribution

2005 ◽  
Author(s):  
F. Pachet ◽  
G. Westermann ◽  
D. Laigre
Keyword(s):  
Data Mining ◽  
Electronic Music ◽  
Music Distribution

Editorial Metadata in Electronic Music Distribution Systems: Between Universalism and Isolationism

2005 ◽  
Vol 34 (2) ◽  
pp. 173-184 ◽  
Author(s):  
François Pachet ◽  
Amaury La Burthe ◽  
Jean-Julien Aucouturier ◽  
Anthony Beurivé
Keyword(s):  
Electronic Music ◽  
Distribution Systems ◽  
Music Distribution

The Cuidado music browser: an end-to-end electronic music distribution system

2006 ◽  
Vol 30 (3) ◽  
pp. 331-349 ◽  
Author(s):  
François Pachet ◽  
Jean-Julien Aucouturier ◽  
Amaury La Burthe ◽  
Aymeric Zils ◽  
Anthony Beurive
Keyword(s):  
Distribution System ◽  
Electronic Music ◽  
End To End ◽  
Music Distribution

Data Mining and Machine Learning

2020 ◽  
Author(s):  
Mohammed J. Zaki ◽  
Wagner Meira, Jr
Keyword(s):  
Machine Learning ◽  
Data Mining

Heart Rate Variability, Emotions, and Music

2010 ◽  
Vol 24 (2) ◽  
pp. 112-119 ◽  
Author(s):  
F. Riganello ◽  
A. Candelieri ◽  
M. Quintieri ◽  
G. Dolce
Keyword(s):  
Data Mining ◽  
Heart Rate ◽  
Heart Rate Variability ◽  
Vegetative State ◽  
Low Frequency ◽  
Emotional Reactions ◽  
Heart Beat ◽  
Healthy Controls ◽  
Frequency Spectra ◽  
Emotional Value

The purpose of the study was to identify significant changes in heart rate variability (an emerging descriptor of emotional conditions; HRV) concomitant to complex auditory stimuli with emotional value (music). In healthy controls, traumatic brain injured (TBI) patients, and subjects in the vegetative state (VS) the heart beat was continuously recorded while the subjects were passively listening to each of four music samples of different authorship. The heart rate (parametric and nonparametric) frequency spectra were computed and the spectra descriptors were processed by data-mining procedures. Data-mining sorted the nu_lf (normalized parameter unit of the spectrum low frequency range) as the significant descriptor by which the healthy controls, TBI patients, and VS subjects’ HRV responses to music could be clustered in classes matching those defined by the controls and TBI patients’ subjective reports. These findings promote the potential for HRV to reflect complex emotional stimuli and suggest that residual emotional reactions continue to occur in VS. HRV descriptors and data-mining appear applicable in brain function research in the absence of consciousness.

Sign in / Sign up

Export Citation Format

Share Document