pitchDescriptives: Pitch descriptives

View source: R/pitchDescriptives.R

pitchDescriptivesR Documentation

Pitch descriptives

Description

Provides common descriptives of time series such as pitch contours, including measures of average / range / variability / slope / inflections etc. Several degrees of smoothing can be applied consecutively. The summaries are produced on the original and log-transformed scales, so this is meant to be used on frequency-related variables in Hz.

Usage

pitchDescriptives(
  x,
  step = NULL,
  timeUnit,
  smoothBW = c(NA, 10, 1),
  inflThres = 0.2,
  extraSummaryFun = c(),
  ref = 16.35,
  plot = FALSE
)

Arguments

x

input: numeric vector, a list of time stamps and values in rows, a dataframe with one row per file and time/pitch values stored as characters (as exported by pitch_app), or path to csv file containing the output of pitch_app or analyze

step

distance between values in s (only needed if input is a vector)

timeUnit

specify whether the time stamps (if any) are in ms or s

smoothBW

a vector of bandwidths (Hz) for consecutive smoothing of input using pitchSmoothPraat; NA = no smoothing

inflThres

minimum difference (in semitones) between consecutive extrema to consider them inflections; to apply a different threshold at each smoothing level, provide inflThres as a vector of the same length as smoothBW; NA = no threshold

extraSummaryFun

additional summary function(s) that take a numeric vector with some NAs and return a single number, eg c('myFun1', 'myFun2')

ref

reference value for transforming Hz to semitones, defaults to C0 (16.35 Hz)

plot

if TRUE, plots the inflections for manual verification

Value

Returns a dataframe with columns containing summaries of one or multiple inputs (one input per row). The descriptives are as follows:

duration

total duration, s

durDefined

duration after omitting leading and trailing NAs

propDefined

proportion of input with non-NA value, eg proportion of voiced frames if the input is pitch

start, start_oct, end, end_oct

the first and last values on the original scale and in octaves above C0 (16.3516 Hz)

mean, median, max, min

average and extreme values on the original scale

mean_oct, median_oct, min_oct, max_oct

same in octaves above C0

time_max, time_min

the location of minimum and maximum relative to durDefined, 0 to 1

range, range_sem, sd, sd_sem

range and standard deviation on the original scale and in semitones

CV

coefficient of variation = sd/mean (provided for historical reasons)

meanSlope, meanSlope_sem

mean slope in Hz/s or semitones/s (NB: does not depend on duration or missing values)

meanAbsSlope, meanAbsSlope_sem

mean absolute slope (modulus, ie rising and falling sections no longer cancel out)

maxAbsSlope, maxAbsSlope_sem

the steepest slope

Examples

x = c(NA, NA, 405, 441, 459, 459, 460, 462, 462, 458, 458, 445, 458, 451,
444, 444, 430, 416, 409, 403, 403, 389, 375, NA, NA, NA, NA, NA, NA, NA, NA,
NA, 183, 677, 677, 846, 883, 886, 924, 938, 883, 946, 846, 911, 826, 826,
788, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 307,
307, 368, 377, 383, 383, 383, 380, 377, 377, 377, 374, 374, 375, 375, 375,
375, 368, 371, 374, 375, 361, 375, 389, 375, 375, 375, 375, 375, 314, 169,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 238, 285, 361, 374, 375, 375,
375, 375, 375, 389, 403, 389, 389, 375, 375, 389, 375, 348, 361, 375, 348,
348, 361, 348, 342, 361, 361, 361, 365, 365, 361, 966, 966, 966, 959, 959,
946, 1021, 1021, 1026, 1086, 1131, 1131, 1146, 1130, 1172, 1240, 1172, 1117,
1103, 1026, 1026, 966, 919, 946, 882, 832, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA)
plot(x, type = 'b')
ci95 = function(x) diff(quantile(na.omit(x), probs = c(.025, .975)))
pd = pitchDescriptives(
  x, step = .025, timeUnit = 's',
  smoothBW = c(NA, 10, 1),   # original + smoothed at 10 Hz and 1 Hz
  inflThres = c(NA, .2, .2), # different for each level of smoothing
  extraSummaryFun = 'ci95',  # user-defined, here 95% coverage interval
  plot = TRUE
)
pd

## Not run: 
# a single file
data(sheep, package = 'seewave')
a = analyze(sheep)
pd1 = pitchDescriptives(a$detailed[, c('time', 'pitch')],
                        timeUnit = 'ms', inflThres = NA, plot = TRUE)
pd2 = pitchDescriptives(a$detailed[, c('time', 'pitch')],
                        timeUnit = 'ms', inflThres = c(0.1, 0.1, .5), plot = TRUE)

# multiple files returned by analyze()
an = analyze('~/Downloads/temp')
pd = pitchDescriptives(an$detailed, timeUnit = 'ms')
pd

# multiple files returned by pitch_app()
pd = pitchDescriptives(
  '~/Downloads/pitch_manual_1708.csv',
  timeUnit = 'ms', smoothBW = c(NA, 2), inflThres = .25)

# a single file, exported from Praat
par(mfrow = c(3, 1))
pd = pitchDescriptives(
  '~/Downloads/F-Hin-Om_jana.wav_F0contour.txt',
  timeUnit = 's', smoothBW = c(NA, 25, 2), inflThres = .25, plot = TRUE)
par(mfrow = c(1, 1))

## End(Not run)

soundgen documentation built on Aug. 14, 2022, 5:05 p.m.