Intended as a tool for familiarization with a dataset,
identification of outliers, and further analyses.
This may also be helpful in describing data to the visually impaired. NOTE: This package requires the installation of a separate standalone synthesizer application. The R functions will send plots to this program, which is where you will "play" your plots. See Details for details.
The standalone application uses QuickTime, without which visual details will not appear.
Details
Package:
audiolyzR
Type:
Package
Version:
0.4-9
Date:
2013-2-16
License:
GPL-2
audiolyzR translates scatterplots, scatterplot matrices, histograms, and (soon) other plots into corresponding audio graphics. You will see that the plots are played either by looping from left to right, or by directing an interactive cursor.
You will have live control over global volume and tempo, along with quality (major vs minor vs augmented, etc.), range of pitches (in case you have trouble hearing particularly high or low notes), and gap between loops.
Things to note and pay attention to while you listen:
1) The X or horizontal axis corresponds to time (not pitch).
2) Pitch corresponds to the Y or vertical axis.
3) Reverb is inversely proportional to correlation (more reverb for less correlation).
4) Synthesizer dryness is mildly related to number of points in a column.
5) Relative note volume is inversely proportional to the number of notes in a neighborhood of each (higher volume for fewer neighbors)
Instructions for the external audiolyzR application:
In order to run audiolyzR, you need to install the appropriate standalone application. The first time you run any audiolyzR command, it will automatically install the appropriate version for your system. If you prefer to download the files yourself: Mac: http://s3.amazonaws.com/audiolyzR/installers/the_audiolyzR_mac_v5.zip
Merabet LB, Pascual-Leone A (2010). "Neural reorganization following sensory loss: the opportunity of change." Nature reviews. Neuroscience, 11(1), 44 to 52. ISSN 1471-0048. doi:10.1038/nrn2758. http://www.ncbi.nlm.nih.gov/pubmed/19935836.
R Core Team (2012). R: A Language and Environment for Statistical Computing. R Foun- dation for Statistical Computing, Vienna, Austria. ISBN 3-900051-07-0, http://www.R-project.org.
Sarkar D (2008). Lattice: Multivariate Data Visualization with R. Springer Science+Business Media.
Stein BE, Stanford TR (2008). "Multisensory integration: current issues from the perspective of the single neuron." Nature reviews. Neuroscience, 9(4), 255 to 66. ISSN 1471-0048. doi: 10.1038/nrn2331. http://www.ncbi.nlm.nih.gov/pubmed/18354398.