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Convert a Praat Intensity tier to a dataframe.

Usage

intensity_to_df(file_name)

Arguments

file_name

string with a filename or path to the Intensity tier

Value

a dataframe with columns: time_start, time_end, Intensity

Author

George Moroz <agricolamz@gmail.com>

Examples

intensity_to_df(system.file("extdata", "test.Intensity", package = "phonfieldwork"))
#>     time_start    time_end intensity
#> 1  0.000000000 0.000000000  39.30749
#> 2  0.008940764 0.008940764  38.87412
#> 3  0.017881527 0.017881527  38.57424
#> 4  0.026822291 0.026822291  37.93917
#> 5  0.035763054 0.035763054  39.22305
#> 6  0.044703818 0.044703818  40.04061
#> 7  0.053644581 0.053644581  38.85294
#> 8  0.062585345 0.062585345  36.54414
#> 9  0.071526108 0.071526108  40.37141
#> 10 0.080466872 0.080466872  47.55616
#> 11 0.089407635 0.089407635  56.62113
#> 12 0.098348399 0.098348399  60.88946
#> 13 0.107289162 0.107289162  61.37729
#> 14 0.116229926 0.116229926  59.38835
#> 15 0.125170689 0.125170689  56.96737
#> 16 0.134111453 0.134111453  55.55835
#> 17 0.143052216 0.143052216  54.26911
#> 18 0.151992980 0.151992980  52.50135
#> 19 0.160933743 0.160933743  51.27701
#> 20 0.169874507 0.169874507  50.54501
#> 21 0.178815270 0.178815270  50.67041
#> 22 0.187756034 0.187756034  51.64555
#> 23 0.196696797 0.196696797  50.55749
#> 24 0.205637561 0.205637561  50.53060
#> 25 0.214578324 0.214578324  52.51058
#> 26 0.223519088 0.223519088  54.85600
#> 27 0.232459852 0.232459852  61.17698
#> 28 0.241400615 0.241400615  65.93068
#> 29 0.250341379 0.250341379  68.14527
#> 30 0.259282142 0.259282142  68.94030
#> 31 0.268222906 0.268222906  69.47599
#> 32 0.277163669 0.277163669  69.66139
#> 33 0.286104433 0.286104433  69.35156
#> 34 0.295045196 0.295045196  69.12312
#> 35 0.303985960 0.303985960  69.41106
#> 36 0.312926723 0.312926723  69.74102
#> 37 0.321867487 0.321867487  69.52651
#> 38 0.330808250 0.330808250  68.86931
#> 39 0.339749014 0.339749014  68.23661
#> 40 0.348689777 0.348689777  68.17743
#> 41 0.357630541 0.357630541  67.71186
#> 42 0.366571304 0.366571304  66.70133
#> 43 0.375512068 0.375512068  65.77517
#> 44 0.384452831 0.384452831  65.40704
#> 45 0.393393595 0.393393595  64.84207
#> 46 0.402334358 0.402334358  63.81003
#> 47 0.411275122 0.411275122  63.33876
#> 48 0.420215885 0.420215885  62.76678
#> 49 0.429156649 0.429156649  61.62731
#> 50 0.438097412 0.438097412  59.56992
#> 51 0.447038176 0.447038176  58.34945
#> 52 0.455978940 0.455978940  58.61335
#> 53 0.464919703 0.464919703  58.46972
#> 54 0.473860467 0.473860467  58.35225
#> 55 0.482801230 0.482801230  58.60761
#> 56 0.491741994 0.491741994  58.54995
#> 57 0.500682757 0.500682757  58.98097
#> 58 0.509623521 0.509623521  59.06485
#> 59 0.518564284 0.518564284  57.20696
#> 60 0.527505048 0.527505048  56.23815
#> 61 0.536445811 0.536445811  55.88090
#> 62 0.545386575 0.545386575  53.39294
#> 63 0.554327338 0.554327338  50.74157
#> 64 0.563268102 0.563268102  51.23953
#> 65 0.572208865 0.572208865  52.11645
#> 66 0.581149629 0.581149629  51.88973
#> 67 0.590090392 0.590090392  51.05982
#> 68 0.599031156 0.599031156  50.36096
#> 69 0.607971919 0.607971919  50.56470
#> 70 0.616912683 0.616912683  51.59961
#> 71 0.625853446 0.625853446  51.62710
#> 72 0.634794210 0.634794210  50.68025
#> 73 0.643734973 0.643734973  49.64369
#> 74 0.652675737 0.652675737  48.73534