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extracts duration and mean pitch
# Get mean pitch and duration
# Frequency altered feedback study
# PraatR documentation: http://www.aaronalbin.com/praatr/tutorial.html
# loop through all the files in a directory
library("PraatR")
library("phonTools")
# define the partcipant/folder/output file name
participant <- "NAME"
condition <- "FAF" # frequency altered feedback
# condition <- "Speech" # own speech
shift.direction <- "DOWN"
# output files are appended
# outputFileName <- paste("NAME", "_VALUES", ".csv", sep="")
# output files are separate
outputFileName <- paste(
participant, "_", condition, "_", shift.direction, ".csv",
sep=""
)
# define output directory
# file.path makes the path OS-agnostic
dirOutput <- file.path("C:", "Users", "E", "Desktop")
# set the working directory
workingDirectory <- file.path(
"C:", "Users", "E", "Desktop", "Chop", participant, condition, shift.direction
)
setwd(workingDirectory)
# define a function to paste dir and filename
FullPath <- function(FileName){
return( paste(workingDirectory, "/", FileName, sep="") )
}
# find all wav files in the working directory
filenames <- list.files(path = workingDirectory, pattern = "*.wav$")
# create empty vectors
duration <- vector()
meanPitch <- vector()
wavFilename <- vector()
# TODO: vectorise to increase the speed
for (i in filenames) {
# Try the wavFile for errors (e.g. empty wav file)
tryit <- try(wavFile <- loadsound(i))
if(inherits(tryit, "try-error")){
print(paste("Error in", i))
# uncomment the lines below to add NAs to the data frame
wavFilename <- append(wavFilename, i)
duration <- append(duration, NA)
meanPitch <- append(meanPitch, NA)
} else {
# save the file name
wavFilename <- append(wavFilename, i)
wavDuration <- as.numeric(praat("Get total duration",
input=FullPath(i),
simplify=TRUE
)
)
# print(wavDuration)
duration <- append(duration, wavDuration)
# create the pitch track
# http://www.fon.hum.uva.nl/praat/manual/Sound__To_Pitch___.html
praat("To Pitch (ac)...",
arguments=list(0, # time step (s)
50, # pitch floor (Hz) - default 75
15, # max number of candidates
"no", # very accurate
0.15, # silence threshold - default 0.03
0.45, # voicing threshold
0.01, # octave cost
0.35, # octave-jump cost
0.14, # voiced/unvoiced cost
300), # pitch ceiling (Hz) - default 600
input=FullPath(i),
output=FullPath("pitch_track"),
overwrite=TRUE
)
# get the minimum pitch
mnPitch <- as.numeric(praat("Get mean...",
arguments=list(0, # time range (s) start (0 = all)
0, # time range (s) end (0 = all)
"Hertz"), # unit
input=FullPath("pitch_track"),
simplify=TRUE
)
)
# print(mnPitch)
meanPitch <- append(meanPitch, mnPitch)
}
}
results <- data.frame(wavFilename,
duration,
meanPitch,
participant,
condition,
shift.direction,
stringsAsFactors = FALSE)
# save to a csv
write.table(results,
file = file.path(dirOutput, outputFileName),
sep=",",
append = TRUE,
row.names = FALSE,
# don't append column names if the file exists
col.names=!file.exists(file.path
(dirOutput, outputFileName)
)
)
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