Select the best analyses using the 'classic' Fast Track method from Praat. Each formant is predicted using a regression model, and the analysis with the smallest . Generates identical output to the autoselect step in Praat, except for no regression information text files are written (for now).
autoselect.classic( formants = NA, order = 5, n_formants = 4, outputpath = NA, subset = NA, progressbar = FALSE, write = TRUE )
| formants | a list of formant data read in with the readformants function, or created using the trackformants function. |
|---|---|
| order | the order of the prediction model. |
| n_formants | the number of formants to optimize for. |
| outputpath | if NA, nothing is written out. If "working", data is written out to the working directory. Any other path may also be specified. |
| subset | a vector indicating a subset of the analyses to be considered. |
| progressbar | if TRUE, a progress bar prints out in the console. |
| write | if TRUE, an RDS file containing selection information is saved to the working directory. |
An object of the class "selection_info". A list containing information about the selection of the winners. See the documentation for readselectioninfo for more information.
if (FALSE) { # load a previous analysis from Praat formants = readformants () # or load a previous analysis saved from R formants = readRDS ('formants.RDS') # or track the formants using R formants = trackformants () # keep results in R winners = autoselect.classic (formants, progressbar = TRUE) # generate Praat compliant data files winners = autoselect.classic (formants, outputpath="working") }