matchPars: Match soundgen pars (experimental)

In soundgen: Sound Synthesis and Acoustic Analysis

Match soundgen pars (experimental)

Description

Attempts to find settings for soundgen that will reproduce an existing sound. The principle is to mutate control parameters, trying to improve fit to target. The currently implemented optimization algorithm is simple hill climbing. Disclaimer: this function is experimental and may or may not work for particular tasks. It is intended as a supplement to - not replacement of - manual optimization. See vignette('sound_generation', package = 'soundgen') for more information.

Usage

matchPars(
  target,
  samplingRate = NULL,
  pars = NULL,
  init = NULL,
  probMutation = 0.25,
  stepVariance = 0.1,
  maxIter = 50,
  minExpectedDelta = 0.001,
  compareSoundsPars = list(),
  verbose = TRUE
)

Arguments

target	the sound we want to reproduce using soundgen: path to a .wav file or numeric vector
samplingRate	sampling rate of target (only needed if target is a numeric vector, rather than a .wav file)
pars	arguments to soundgen that we are attempting to optimize
init	a list of initial values for the optimized parameters pars and the values of other arguments to soundgen that are fixed at non-default values (if any)
probMutation	the probability of a parameter mutating per iteration
stepVariance	scale factor for calculating the size of mutations
maxIter	maximum number of mutated sounds produced without improving the fit to target
minExpectedDelta	minimum improvement in fit to target required to accept the new sound candidate
compareSoundsPars	a list of control parameters passed to compareSounds
verbose	if TRUE, plays back the accepted candidate at each iteration and reports the outcome

Value

Returns a list of length 2: $history contains the tried parameter values together with their fit to target ($history$sim), and $pars contains a list of the final - hopefully the best - parameter settings.

Examples

## Not run: 
target = soundgen(sylLen = 600, pitch = c(300, 200),
                  rolloff = -15, play = TRUE, plot = TRUE)
# we hope to reproduce this sound

# Match pars based on acoustic analysis alone, without any optimization.
# This *MAY* match temporal structure, pitch, and stationary formants
m1 = matchPars(target = target,
               samplingRate = 16000,
               maxIter = 0,  # no optimization, only acoustic analysis
               verbose = TRUE)
cand1 = do.call(soundgen, c(m1$pars, list(
  temperature = 0.001, play = TRUE, plot = TRUE)))

# Try to improve the match by optimizing rolloff
# (this may take a few minutes to run, and the results may vary)
m2 = matchPars(target = target,
               samplingRate = 16000,
               pars = 'rolloff',
               maxIter = 100,
               verbose = TRUE)
# rolloff should be moving from default (-9) to target (-15):
sapply(m2$history, function(x) x$pars$rolloff)
cand2 = do.call(soundgen, c(m2$pars, list(play = TRUE, plot = TRUE)))

## End(Not run)

soundgen documentation built on Sept. 12, 2024, 6:29 a.m.