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#!/usr/bin/env python

import glob, os
for file in sorted(glob.glob("*.wav")):
    print("#"*40)
    print(file)
    os.system("python audioAnalysis.py silenceRemoval -i " + file + " --smoothing 0.2 --weight 0.1")

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#!/usr/bin/env r

## load pitch files extracted from Praat and pull key information

# take input from the command line
f <- argv

# load packages and hide messages
library(dplyr)
library(rPraat)

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clearinfo

# uncomment for a point-and-click version (then the next two lines should be commented out)
#inDir$ = chooseDirectory$: "Choose the folder containing your wav files"

wd$ = "./"
inDir$ = wd$

# create a list of all wav files in the chosen directory
inDirWild$ = inDir$ + "*.wav"

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library(RCurl)

# download the R code
script <- getURL("https://raw.githubusercontent.com/usagi5886/dsp/master/Spectrogram().r",
                 ssl.verifypeer = FALSE)
# load it as a function
eval(parse(text = script))

library(audio)
# download the wav file

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library(hht)

data(PortFosterEvent)

dt <- mean(diff(tt))

ft <- list()
ft$nfft <- 4096
ft$ns <- 30
ft$nov <- 29

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library(warbleR)

# load and save data
data(list = c("Phae.long1", "Phae.long2","selec.table"))
writeWave(Phae.long1, "Phae.long1.wav")

# make spectrograms (saves the files in the working directory)
specreator(X = selec.table, flim = c(0, 11), res = 300, mar = 0.05, wl = 300)

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library(soundgen)

# synthesize a sound 1 s long, with gradually increasing hissing noise
sound = soundgen(sylLen = 1000,
                 temperature = 0.001,
                 noiseAnchors = list(
                   time = c(0, 1300),
                   value = c(-120, 0)),
                 formantsNoise = list(
                   f1 = list(

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library(signal)

specgram(chirp(seq(-2, 15, by = 0.001), 400, 10, 100, 'quadratic'))

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library(ggplot2)

## first layer
v <- ggspectro(tico, ovlp = 50)

## using geom_tile ##
v + geom_tile(aes(fill = amplitude)) + stat_contour()

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library(seewave)

data(tico)
spectro(tico)