jargon.js

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// You need to make keys of this object lower case.
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export const definitions = {
	'audio descriptor':
		"Audio descriptors, or features, are values or labels that represent characteristics of an audio signal.  Descriptors can be computed automatically with machine listening or manually assigned by a human. They can correlate with a perceptual quality of a sound, such as its loudness or brightness, but shouldn't be confused as actually representing these perceptual qualities (because a signal is not the same thing as a sound!). Descriptors can also sometimes be used to try an capture more complex sonic or musical concepts, such as genre; however, because these more complex concepts always have social and cultural dimensions, one should be conscious of the limits  on what can be inferred from isolated and decontextualised signals.",
	'interquartile range':
		"The range between the 25th and 75th <a href='https://learn.flucoma.org/reference/bufstats'>percentiles</a>. 50% of the data will fall within this range.",
	quartile:
		'One quarter of the values in a dimension of data. Usually between evenly divided percentiles: 0th to 25th, 25th to 50th, 50th to 75th, or 75th to 100th percentiles.',
	quartiles:
		'One quarter of the values in a dimension of data. Usually between evenly divided percentiles: 0th to 25th, 25th to 50th, 50th to 75th, or 75th to 100th percentiles.',
	spectrum: "See the <a href='https://en.wikipedia.org/wiki/Spectrogram'>wikipedia article</a>.",
	mean: 'The average value of the data. This is calculated by adding up all the numbers and the dividing by how many numbers there are.',
	median: 'The value at or below which 50% of the values in the data will fall, also called the 50th percentile.',
	mode: 'The value that occurs most frequently in a set of data.',
	glissandi: 'A continuous slide upwards or downwards between two notes.',
	'euclidean distance':
		'Using the Pythagorean Theorem (but often in more than two dimensions) to compute the distance between any two points in a multi-dimensional space.',
	logarithmic:
		"A logarithm is the opposite of an exponent. With exponentiation (y = x^2), as 'x' gets bigger, 'y' keeps getting 'exponetially bigger'. With a logarithm (y = log(x)), as x gets bigger, y continues to grow but at a slower and slower rate. See the <a href='https://en.wikipedia.org/wiki/Logarithm'>Wikipedia article</a> for more. <p><a href='https://commons.wikimedia.org/wiki/File:Logarithm_plots.png#/media/File:Logarithm_plots.png'><img src='https://upload.wikimedia.org/wikipedia/commons/thumb/8/81/Logarithm_plots.png/1200px-Logarithm_plots.png' alt='Logarithm plots' width='300px'></a><br>By Richard F. Lyon<a href='https://creativecommons.org/licenses/by-sa/3.0' title='Creative Commons Attribution-Share Alike 3.0'>CC BY-SA 3.0</a>, <a href='https://commons.wikimedia.org/w/index.php?curid=13257335'>Link</a></p>"
};