FAVE Remeasure module

class fave.extract.remeasure.VowelMeasurement

represents a vowel measurement

fave.extract.remeasure.calculateVowelMeans(vowels)

calculates [means] and [covariance matrices] for each vowel class. It returns these as numpy arrays in dictionaries indexed by the vowel class.

fave.extract.remeasure.createVowelDictionary(measurements)

Creates a dictionary of F1, F2, B1, B3 and Duration observations by vowel type. vowel index indicates the index in lines[x] which should be taken as identifying vowel categories.

fave.extract.remeasure.excludeOutliers(vowels, vowelMeans, vowelCovs)

Finds outliers and excludes them.

fave.extract.remeasure.loadfile(file)

Loads an extractFormants file. Returns formatted list of lists.

fave.extract.remeasure.output(remeasurements)

writes measurements to file according to selected output format

fave.extract.remeasure.pruneVowels(vowels, vowel, vowelMeans, vowelCovs, outlie)

Tries to prune outlier vowels, making sure enough tokens are left to calculate mahalanobis distance.

fave.extract.remeasure.repredictF1F2(measurements, vowelMeans, vowelCovs, vowels)

Predicts F1 and F2 from the speaker’s own vowel distributions based on the mahalanobis distance.