Normalises speech data
norm(data, speakerlabs, type = "gerst", rescale = FALSE)Normalised values of data are returned, having the same structure as data.
A matrix of data. Can be either an n-columned matrix or a
trackdata object as returned by track.
A parallel vector of speaker labels.
The type of extrinsic normalisation to be performed on data.
type can be "nearey", "cen", "lob", "gerst"
(default), for normalisation according to Nearey, centroid method, Lobanov,
or Gerstman.
Currently only works for Lobanov normalisation. The normalised values are multiplied by the standard deviation and then the mean is added, where the standard deviation and mean are across all original speakers' unnormalised data.
Types of normalisation: "nearey", Nearey : Find the log of each data
element and subtract from each the mean of the logarithmic data.
"cen", centroid: Find the mean of the data column and subtract it
from each data element in that column. "lob", Lobanov: Find the
mean and standard deviation of the data. Subtract the mean from each data
element and divide each result by the standard deviation. "gerst",
Gerstman: Subtract from the data the minimum formant value then divide by
the formant range.
track