Carrying Out a Folder Analysis Using FastTrackR

Load the fasttrackr R package.

library(fasttrackr)

And change the working directory to wherever you would like all your output files to be.

## change to working directory
setwd("C:/myworkingdirectory/")

For this example I am going to use the example wav and TextGrid files included in Fast TrackR. I am going to write these out to the working directory so that the analysis will be just like one carried out using local wav and TextGrid files.

wav_example
tuneR::writeWave(wav_example, "rainbowpassage.wav")

textgrid_example[1:10]
writeLines(textgrid_example, "rainbowpassage.TextGrid")

Then I extract the stressed vowels from the recording, using the TextGrid. The output of the extraction is saved in RDS files to the working directory.

extractvowels ("rainbowpassage.TextGrid", "rainbowpassage.wav", segmenttier=2,wordtier=1,stress = 1)

The formant tracking function relies on the RDS files in the working directory created in the previous step, although they can also be provided directly to the function.

formants = trackformants.folder (from = 4500, to = 6500, nsteps = 20)

Next, we select the best analysis for each file, again relying on the RDS files in the working directory.

selectioninfo = autoselect.classic()

After picking the best analysis, we get the winning analyses.

ff_data = getwinners()

Finally, we aggregate the data.

aggregated = aggregatedata (csvs = ff_data)

We can plot the aggregated data.

par (mfrow = c(1,1), mar = c(4,4,1,1))
ft.lines(aggregated, xformant=2,yformant=1, revaxes = TRUE, logaxes=FALSE)
ft.arrows(aggregated, xformant=2,yformant=1, revaxes = TRUE, logaxes=FALSE)
ft.points(aggregated, xformant=2,yformant=1, revaxes = TRUE, logaxes=FALSE)

And make figures of the competing analyses or of the winning analysis.

makecomparisonplots()
makewinnerplots(csvs = ff_data)