Parametric source-filter synthesis of harmonic-noise signals, such as animal vocalizations and human voice, with control over pitch, formants, noise, amplitude modulation, nonlinear phenomena, and morphing. General signal processing tools for audio analysis and manipulation: pitch tracking, formant and vocal tract length estimation, reassigned and auditory spectrograms, modulation spectra and psychoacoustic roughness, self-similarity and surprisal, audio segmentation, pitch and formant shifting, etc. Includes four interactive web apps for audio synthesis, annotation, formant analysis, and manually correcting pitch contours.

Key functions

Visualization

spectrogram Ordinary (STFT) spectrograms
audSpectrogram Auditory spectrograms
modulationSpectrum Modulation spectra and roughness (see Anikin 2025)
ssm Self-similarity matrices, acoustic novelty (see Anikin 2026)
phasegram Nonlinear analysis, phasegrams (see Anikin & Herbst 2025)

Acoustic analysis

analyze General-purpose acoustic analysis (extracts nearly everything: spectral descriptives, pitch, formants, loudness, roughness, …)
segment Audio segmentation, analysis of rhythm and temporal structure of sequences
getSurprisal Shannon and autocorrelation-based surprisal, Bayesian surprise (see Anikin 2026)
estimateVTL, schwa Formant analysis (see Anikin et al. 2024)

Interactive acoustic analysis

pitch_app Manually corrected formant measurement
formant_app Manually corrected pitch tracking
annotation_app Audio annotation

Sound synthesis

soundgen The main function for sound and voice synthesis (see Anikin 2019)
soundgen_app Interactive version of the soundgen() function
morph Morphing of two sounds based on their soundgen code

Sound modification

normalizeFolder Peak / RMS etc normalization of recordings
timeStretch, shiftPitch, prosody, shiftFormants Selective modification of fundamental frequency, duration, and/or resonance frequency
noiseRemoval, compressor, addAM, resample, etc: various audio effects

Vignettes

References

Anikin, A. (2019). Soundgen: an open-source tool for synthesizing nonverbal vocalizations. Behavior Research Methods, 51(2), 778-792.
Anikin, A., Barreda, S. & Reby, D. (2024) A practical guide to calculating vocal tract length and scale-invariant formant patterns. Behavior Research Methods 56, 5588–5604.
Anikin, A. (2025) Acoustic estimation of voice roughness. Attention, Perception, & Psychophysics 87: 1771–1787.
Anikin, A. & Herbst, C.T. (2025) How to analyze and manipulate nonlinear phenomena in voice recordings. Philosophical Transactions B 380: 20240003.
Anikin, A. (2026) Measuring surprisal in sound sequences. Behavior Research Methods.

Example of sound synthesis

Use the soundgen() function to create a breathy moan:

s = soundgen(
  sylLen = 230,               # duration of voiced part, ms
  pitch = c(305, 280),        # pitch, Hz (goes down from 305 to 380 Hz)
  ampl = c(0, -20),           # amplitude, dB (gradual fade-out by 20 dB)
  rolloff = -30,              # strong f0, weak harmonics
  temperature = 0.05,         # some stochasticity in generation
  formants = c(260, 960, 1500, 2200,  # F1-F8 formant frequencies, Hz
               2600, 3600, 4200, 4500),
  noise = data.frame(
    time = c(-50, 120, 700),  # time of noise anchors
    value = c(-25, -15, -40)   # noise amplitude, dB
  ),
  rolloffNoise = 0,           # flat noise spectrum before adding formants
  addSilence = 0, samplingRate = 44100, pitchSamplingRate = 44100,
  plot = TRUE, osc = TRUE, ylim = c(0, 6)
)

Example of acoustic analysis

Use the analyze() function to detect pitch and obtain other spectral descriptives of the sound we have just synthesized:

a = analyze(s, 44100, plot = TRUE, ylim = c(0, 6))
#> The sound is too short to be analyzed with amRes = 1 Hz. Actual amRes ~=  1.31

a$detailed[1:5, c('time', 'pitch', 'HNR', 'ampl', 'loudness')]
#>        time    pitch       HNR       ampl  loudness
#> 1  25.00000       NA        NA 0.03313867  6.039053
#> 2  49.98866 298.2525  5.656488 0.18586389 14.131545
#> 3  74.97732 304.5555 15.080634 0.41149933 23.273527
#> 4  99.96599 300.9743 17.070995 0.53578982 27.618641
#> 5 124.95465 296.9162 14.551249 0.49568060 26.568438
colnames(a$detailed)
#>  [1] "duration"           "duration_noSilence" "time"               "amEnvDep"          
#>  [5] "amEnvDepVoiced"     "amEnvFreq"          "amEnvFreqVoiced"    "amEnvPurity"       
#>  [9] "amEnvPurityVoiced"  "amMsFreq"           "amMsFreqVoiced"     "amMsPurity"        
#> [13] "amMsPurityVoiced"   "ampl"               "ampl_noSilence"     "amplVoiced"        
#> [17] "CPP"                "dom"                "domVoiced"          "entropySh"         
#> [21] "entropyShVoiced"    "entropyW"           "entropyWVoiced"     "epoch"             
#> [25] "f1_freq"            "f1_width"           "f2_freq"            "f2_width"          
#> [29] "f3_freq"            "f3_width"           "fluctuation"        "fluctuationVoiced" 
#> [33] "flux"               "fmDep"              "fmFreq"             "fmPurity"          
#> [37] "harmEnergy"         "harmHeight"         "HNR"                "HNRVoiced"         
#> [41] "loudness"           "loudnessVoiced"     "novelty"            "noveltyVoiced"     
#> [45] "peakFreq"           "peakFreqVoiced"     "pitch"              "quartile25"        
#> [49] "quartile25Voiced"   "quartile50"         "quartile50Voiced"   "quartile75"        
#> [53] "quartile75Voiced"   "roughness"          "roughnessVoiced"    "sharpness"         
#> [57] "sharpnessVoiced"    "specCentroid"       "specCentroidVoiced" "specSlope"         
#> [61] "specSlopeVoiced"    "subDep"             "subRatio"           "voiced"