ravetools (version 0.2.3)

gammatone_fast: Apply gamma-tone filters to obtain auditory envelopes

Description

Apply gamma-tone filters to obtain auditory envelopes

Usage

gammatone_fast(
  x,
  sample_rate,
  center_frequencies,
  n_bands,
  use_hilbert = TRUE,
  downsample = NA,
  downsample_before_hilbert = FALSE
)

Value

A file-array object of filtered and potentially down-sampled data; see 'Examples' on how to use this function.

Arguments

x

a numeric vector or matrix; if x is a matrix, it should be column-major (each column is a sound track)

sample_rate

sampling frequency

center_frequencies

center frequencies at which the envelopes will be derived; can be either a length of two defining the lower and upper bound, and using n_bands to interpolate automatically, or a length of multiple, with the frequencies specified explicitly

n_bands

number of the center frequencies, can be missing if center_frequencies is explicit and no interpolation is needed; if specified, then the frequencies will be interpolated using equivalent rectangular bandwidth rate ('ERB')

use_hilbert

whether to apply 'Hilbert' transform; default is true, which calculates the magnitude; set to false when only the filter is needed

downsample

whether to down-sample the envelopes after the filters; default is NA (no down-sample).

downsample_before_hilbert

whether the down-sample happens before or after the 'Hilbert' transform so speed up the computation if the signal is too long; only used when downsample is greater than 1; default is FALSE. Use with caution, especially when the voice center frequency is close to the 'Nyquist' frequency. However, if used properly, there will be significant performance boost on large signals with high sampling rates

Examples

fs <- 4000
time <- seq_len(8000) / fs
x <- sin(160 * pi * time) +
  sin(1000 * pi * time) * dnorm(time, mean = 1, sd = 0.1) +
  0.5 * rnorm(length(time))

# envelope
result <- gammatone_fast(
  x,
  sample_rate = fs,
  center_frequencies = c(20, 1000),
  n_bands = 128,

  # default downsample happens after hilbert
  downsample = 40
)


oldpar <- par(mfrow = c(2, 1))

plot(
  time,
  x,
  type = "l",
  xlab = "Time",
  ylab = "",
  main = "Original mixed 80Hz and 500Hz"
)

# only one channel
envelope <- subset(result, Channel ~ Channel == 1, drop = TRUE)
dnames <-  dimnames(envelope)
image(
  x = as.numeric(dnames$Time),
  y = as.numeric(dnames$Frequency),
  z = envelope,
  xlab = "Time",
  ylab = "Frequency",
  main = "Envelope from 20Hz to 1000Hz"
)



par(oldpar) # reset graphics state